do not use simd neon intrinsics on x86 (#2893)

.github/actions/build-cuda-release/action.yml

@@ -1,6 +1,15 @@
 name: 'Build CUDA wheel'
 description: 'Build CUDA wheel'
 
+inputs:
+  arch:
+    description: 'Platform architecture tag'
+    required: true
+    type: choice
+    options:
+      - x86_64
+      - aarch64
+
 runs:
   using: "composite"
   steps:
@@ -12,4 +21,4 @@ runs:
         pip install auditwheel build patchelf setuptools
         python setup.py clean --all
         MLX_BUILD_STAGE=2 python -m build -w
-        bash python/scripts/repair_cuda.sh
+        bash python/scripts/repair_cuda.sh ${{ inputs.arch }}

.github/actions/setup-linux/action.yml

@@ -15,6 +15,7 @@ runs:
   using: "composite"
   steps:
     - name: Use ccache
+      if: ${{ runner.arch == 'x86_64' }}
       uses: hendrikmuhs/ccache-action@v1.2
       with:
         key: ccache-${{ runner.os }}-${{ runner.arch }}-${{ inputs.toolkit }}-py${{ inputs.python-version }}

.github/workflows/release.yml

@@ -128,7 +128,11 @@ jobs:
 
   build_cuda_release:
     if: github.repository == 'ml-explore/mlx'
-    runs-on: ubuntu-22-large
+    strategy:
+      matrix:
+        arch: ['x86_64', 'aarch64']
+        toolkit: ['cuda-12.9', 'cuda-13.0']
+    runs-on: ${{ matrix.arch == 'x86_64' && 'ubuntu-22-large' || 'ubuntu-22-large-arm' }}
     env:
       PYPI_RELEASE: 1
       DEV_RELEASE: ${{ github.event.inputs.dev_release == 'true' && 1 || 0 }}
@@ -136,9 +140,11 @@ jobs:
       - uses: actions/checkout@v6
       - uses: ./.github/actions/setup-linux
         with:
-          toolkit: 'cuda-12.9'
+          toolkit: ${{ matrix.toolkit }}
       - name: Build Python package
         uses: ./.github/actions/build-cuda-release
+        with:
+          arch: ${{ matrix.arch }}
       - name: Upload artifacts
         uses: actions/upload-artifact@v5
         with:

CMakeLists.txt

@@ -119,10 +119,6 @@ if(MLX_BUILD_METAL)
     COMMAND zsh "-c" "/usr/bin/xcrun -sdk macosx --show-sdk-version"
     OUTPUT_VARIABLE MACOS_SDK_VERSION
     OUTPUT_STRIP_TRAILING_WHITESPACE COMMAND_ERROR_IS_FATAL ANY)
-  execute_process(
-    COMMAND zsh "-c" "/usr/bin/xcrun -sdk macosx --show-sdk-path"
-    OUTPUT_VARIABLE CMAKE_OSX_SYSROOT
-    OUTPUT_STRIP_TRAILING_WHITESPACE COMMAND_ERROR_IS_FATAL ANY)
 
   if(${MACOS_SDK_VERSION} LESS 14.0)
     message(
@@ -277,7 +273,7 @@ target_link_libraries(mlx PRIVATE $<BUILD_INTERFACE:fmt::fmt-header-only>)
 if(MLX_BUILD_PYTHON_BINDINGS)
   message(STATUS "Building Python bindings.")
   find_package(
-    Python 3.8
+    Python 3.10
     COMPONENTS Interpreter Development.Module
     REQUIRED)
   execute_process(

docs/src/install.rst

@@ -29,17 +29,20 @@ MLX has a CUDA backend which you can install with:
 
 .. code-block:: shell
 
-    pip install mlx[cuda]
+    pip install mlx[cuda12]
+
 
 To install the CUDA package from PyPi your system must meet the following
 requirements:
 
-- Nvidia architecture >= SM 7.0 (Volta)
+- Nvidia architecture >= SM 7.5
 - Nvidia driver >= 550.54.14
 - CUDA toolkit >= 12.0
 - Linux distribution with glibc >= 2.35
 - Python >= 3.10
 
+For CUDA 13 use ``pip install mlx[cuda13]``. The CUDA 13 package requires
+an Nvidia driver >= 580 or an appropriate CUDA compatibility package.
 
 CPU-only (Linux)
 ^^^^^^^^^^^^^^^^

docs/src/usage/indexing.rst

@@ -186,7 +186,7 @@ Boolean masks follow NumPy semantics:
 .. code-block:: shell
 
    >>> a = mx.arange(1000).reshape(10, 10, 10)
-   >>> a[mx.random.randn(10, 10) > 0.0] = 0  # valid: mask covers axes 0 and 1
+   >>> a[mx.random.normal((10, 10)) > 0.0] = 0  # valid: mask covers axes 0 and 1
 
 The mask of shape ``(10, 10)`` applies to the first two axes, so ``a[mask]``
 selects the 1-D slices ``a[i, j, :]`` where ``mask[i, j]`` is ``True``.

mlx/CMakeLists.txt

@@ -1,7 +1,6 @@
 target_sources(
   mlx
-  PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/allocator.cpp
+  PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/array.cpp
-          ${CMAKE_CURRENT_SOURCE_DIR}/array.cpp
           ${CMAKE_CURRENT_SOURCE_DIR}/compile.cpp
           ${CMAKE_CURRENT_SOURCE_DIR}/device.cpp
           ${CMAKE_CURRENT_SOURCE_DIR}/dtype.cpp

mlx/allocator.cpp

@@ -1,24 +0,0 @@
-// Copyright © 2023 Apple Inc.
-
-#include <cstdlib>
-#include <sstream>
-
-#include "mlx/allocator.h"
-
-namespace mlx::core::allocator {
-
-Buffer malloc(size_t size) {
-  auto buffer = allocator().malloc(size);
-  if (size && !buffer.ptr()) {
-    std::ostringstream msg;
-    msg << "[malloc] Unable to allocate " << size << " bytes.";
-    throw std::runtime_error(msg.str());
-  }
-  return buffer;
-}
-
-void free(Buffer buffer) {
-  allocator().free(buffer);
-}
-
-} // namespace mlx::core::allocator

mlx/allocator.h

@@ -28,16 +28,16 @@ class Buffer {
   };
 };
 
-Buffer malloc(size_t size);
-
-void free(Buffer buffer);
-
 class Allocator {
   /** Abstract base class for a memory allocator. */
  public:
   virtual Buffer malloc(size_t size) = 0;
   virtual void free(Buffer buffer) = 0;
   virtual size_t size(Buffer buffer) const = 0;
+  virtual Buffer make_buffer(void* ptr, size_t size) {
+    return Buffer{nullptr};
+  };
+  virtual void release(Buffer buffer) {}
 
   Allocator() = default;
   Allocator(const Allocator& other) = delete;
@@ -49,4 +49,25 @@ class Allocator {
 
 Allocator& allocator();
 
+inline Buffer malloc(size_t size) {
+  return allocator().malloc(size);
+}
+
+inline void free(Buffer buffer) {
+  allocator().free(buffer);
+}
+
+// Make a Buffer from a raw pointer of the given size without a copy.  If a
+// no-copy conversion is not possible then the returned buffer.ptr() will be
+// nullptr. Any buffer created with this function must be released with
+// release(buffer)
+inline Buffer make_buffer(void* ptr, size_t size) {
+  return allocator().make_buffer(ptr, size);
+};
+
+// Release a buffer from the allocator made with make_buffer
+inline void release(Buffer buffer) {
+  allocator().release(buffer);
+}
+
 } // namespace mlx::core::allocator

mlx/array.cpp

@@ -82,6 +82,28 @@ array::array(std::initializer_list<int> data, Dtype dtype)
   init(data.begin());
 }
 
+array::array(
+    void* data,
+    Shape shape,
+    Dtype dtype,
+    const std::function<void(void*)>& deleter)
+    : array_desc_(std::make_shared<ArrayDesc>(std::move(shape), dtype)) {
+  auto buffer = allocator::make_buffer(data, nbytes());
+  if (buffer.ptr() == nullptr) {
+    set_data(allocator::malloc(nbytes()));
+    auto ptr = static_cast<char*>(data);
+    std::copy(ptr, ptr + nbytes(), this->data<char>());
+    deleter(data);
+  } else {
+    auto wrapped_deleter = [deleter](allocator::Buffer buffer) {
+      auto ptr = buffer.ptr();
+      allocator::release(buffer);
+      return deleter(ptr);
+    };
+    set_data(buffer, std::move(wrapped_deleter));
+  }
+}
+
 /* Build an array from a shared buffer */
 array::array(allocator::Buffer data, Shape shape, Dtype dtype, Deleter deleter)
     : array_desc_(std::make_shared<ArrayDesc>(std::move(shape), dtype)) {

mlx/array.h

@@ -57,6 +57,16 @@ class array {
       Shape shape,
       Dtype dtype = TypeToDtype<T>());
 
+  /* Build an array from a raw pointer. The constructor will attempt to use the
+   * input data without a copy. The deleter will be called when the array no
+   * longer needs the underlying memory - after the array is destroyed in the
+   * no-copy case and after the copy otherwise. */
+  explicit array(
+      void* data,
+      Shape shape,
+      Dtype dtype,
+      const std::function<void(void*)>& deleter);
+
   /* Build an array from a buffer */
   explicit array(
       allocator::Buffer data,

mlx/backend/cpu/simd/type.h

@@ -3,5 +3,9 @@
 #include "mlx/backend/cpu/simd/base_simd.h"
 
 #ifdef MLX_USE_ACCELERATE
+#if defined(__x86_64__)
+// the accelerate_simd implementation require neon -- use base implementation
+#else
 #include "mlx/backend/cpu/simd/accelerate_simd.h"
 #endif
+#endif

mlx/backend/cuda/allocator.cpp

@@ -20,6 +20,19 @@ constexpr int page_size = 16384;
 // Any allocations smaller than this will try to use the small pool
 constexpr int small_block_size = 8;
 
+#if CUDART_VERSION >= 13000
+inline cudaMemLocation cuda_mem_loc(int i) {
+  cudaMemLocation loc;
+  loc.type = cudaMemLocationTypeDevice;
+  loc.id = i;
+  return loc;
+}
+#else
+inline int cuda_mem_loc(int i) {
+  return i;
+}
+#endif // CUDART_VERSION >= 13000
+
 // The small pool size in bytes. This should be a multiple of the host page
 // size and small_block_size.
 constexpr int small_pool_size = 4 * page_size;
@@ -35,13 +48,7 @@ SmallSizePool::SmallSizePool() {
   int device_count = 0;
   CHECK_CUDA_ERROR(cudaGetDeviceCount(&device_count));
   for (int i = 0; i < device_count; ++i) {
-#if CUDART_VERSION >= 13000
+    auto loc = cuda_mem_loc(i);
-    cudaMemLocation loc;
-    loc.type = cudaMemLocationTypeDevice;
-    loc.id = i;
-#else
-    int loc = i;
-#endif // CUDART_VERSION >= 13000
     CHECK_CUDA_ERROR(
         cudaMemAdvise(data_, small_pool_size, cudaMemAdviseSetAccessedBy, loc));
   }
@@ -90,9 +97,10 @@ CudaAllocator::CudaAllocator()
           page_size,
           [](CudaBuffer* buf) { return buf->size; },
           [this](CudaBuffer* buf) { cuda_free(buf); }) {
-  size_t free, total;
+  size_t free;
-  CHECK_CUDA_ERROR(cudaMemGetInfo(&free, &total));
+  CHECK_CUDA_ERROR(cudaMemGetInfo(&free, &total_memory_));
-  memory_limit_ = total * 0.9;
+  memory_limit_ = total_memory_ * 0.95;
+  free_limit_ = total_memory_ - memory_limit_;
   max_pool_size_ = memory_limit_;
 
   int device_count = 0;
@@ -104,6 +112,10 @@ CudaAllocator::CudaAllocator()
     cudaStream_t s;
     CHECK_CUDA_ERROR(cudaStreamCreateWithFlags(&s, cudaStreamNonBlocking));
     free_streams_.push_back(s);
+
+    cudaMemPool_t mem_pool;
+    CHECK_CUDA_ERROR(cudaDeviceGetDefaultMemPool(&mem_pool, i));
+    mem_pools_.push_back(mem_pool);
   }
   CHECK_CUDA_ERROR(cudaSetDevice(curr));
 }
@@ -154,23 +166,35 @@ CudaAllocator::malloc_async(size_t size, int device, cudaStream_t stream) {
     }
     lock.unlock();
     if (!buf) {
-      cudaError_t err;
       void* data = nullptr;
       if (device == -1) {
-        err = cudaMallocManaged(&data, size);
+        CHECK_CUDA_ERROR(cudaMallocManaged(&data, size));
       } else {
-        err = cudaMallocAsync(&data, size, stream);
+        CHECK_CUDA_ERROR(cudaMallocAsync(&data, size, stream));
-      }
-      if (err != cudaSuccess && err != cudaErrorMemoryAllocation) {
-        throw std::runtime_error(fmt::format(
-            "cudaMallocManaged failed: {}.", cudaGetErrorString(err)));
       }
       if (!data) {
-        return Buffer{nullptr};
+        std::ostringstream msg;
+        msg << "[malloc] Unable to allocate " << size << " bytes.";
+        throw std::runtime_error(msg.str());
       }
       buf = new CudaBuffer{data, size, device};
     }
     lock.lock();
+
+    // If any cuda memory pool has too much reserved memory, clear some
+    // memory from the cache. This prevents graph / kernel execution failing
+    // from OOM
+    if (get_cache_memory() > 0) {
+      for (auto p : mem_pools_) {
+        size_t used = 0;
+        CHECK_CUDA_ERROR(cudaMemPoolGetAttribute(
+            p, cudaMemPoolAttrReservedMemCurrent, &used));
+        if (used > (total_memory_ - free_limit_)) {
+          buffer_cache_.release_cached_buffers(free_limit_);
+          break;
+        }
+      }
+    }
   }
   active_memory_ += buf->size;
   peak_memory_ = std::max(active_memory_, peak_memory_);

mlx/backend/cuda/allocator.h

@@ -71,11 +71,14 @@ class CudaAllocator : public allocator::Allocator {
 
   std::mutex mutex_;
   size_t memory_limit_;
+  size_t free_limit_;
+  size_t total_memory_;
   size_t max_pool_size_;
   BufferCache<CudaBuffer> buffer_cache_;
   size_t active_memory_{0};
   size_t peak_memory_{0};
   std::vector<cudaStream_t> free_streams_;
+  std::vector<cudaMemPool_t> mem_pools_;
   SmallSizePool scalar_pool_;
 };
 

mlx/backend/cuda/copy/copy_general_input.cu

@@ -95,11 +95,14 @@ void copy_general_input(
             const InType* in_ptr = gpu_ptr<InType>(in) + offset_in;
             OutType* out_ptr = gpu_ptr<OutType>(out) + offset_out;
             int ndim = shape.size();
-            int work_per_thread = 1;
+
+            int work_per_thread = 8;
             auto dim0 = ndim > 0 ? shape.back() : 1;
             auto rest = out.size() / dim0;
-            if (dim0 >= 4) {
+            if (dim0 >= 4 && dim0 < 8) {
               work_per_thread = 4;
+            } else if (dim0 < 4) {
+              work_per_thread = 1;
             }
             dim0 = (dim0 + work_per_thread - 1) / work_per_thread;
             auto block_dims = get_block_dims(dim0, rest, 1);
@@ -110,7 +113,10 @@ void copy_general_input(
               dispatch_1_2_3(ndim, [&](auto dims_constant) {
                 auto kernel =
                     cu::copy_g_nd<InType, OutType, IdxT, dims_constant(), 1>;
-                if (work_per_thread == 4) {
+                if (work_per_thread == 8) {
+                  kernel =
+                      cu::copy_g_nd<InType, OutType, IdxT, dims_constant(), 8>;
+                } else if (work_per_thread == 4) {
                   kernel =
                       cu::copy_g_nd<InType, OutType, IdxT, dims_constant(), 4>;
                 }
@@ -127,7 +133,9 @@ void copy_general_input(
               });
             } else { // ndim >= 4
               auto kernel = cu::copy_g<InType, OutType, IdxT, 1>;
-              if (work_per_thread == 4) {
+              if (work_per_thread == 8) {
+                kernel = cu::copy_g<InType, OutType, IdxT, 8>;
+              } else if (work_per_thread == 4) {
                 kernel = cu::copy_g<InType, OutType, IdxT, 4>;
               }
               encoder.add_kernel_node(

mlx/backend/cuda/device.cpp

@@ -318,46 +318,64 @@ void CommandEncoder::add_kernel_node(const CUDA_KERNEL_NODE_PARAMS& params) {
   insert_graph_dependencies(GraphNode{node, "K"});
 }
 
-bool is_graph_updatable(cudaGraph_t graph, int& cluster_dim_x) {
+std::pair<std::string, bool> subgraph_to_key(cudaGraph_t graph) {
-  // CUDA graphs do not get updated correctly if a kernel node getting updated
+  // Constructs a key representing the nodes of a sub-graph.
-  // has a different cluster shape than the node it's being updated with.
+  // Also checks if the sub-graph is updatable as CUDA graphs do not get
+  // updated correctly if a kernel node getting updated has a different cluster
+  // shape than the node it's being updated with.
+  std::string key = "(";
   size_t num_nodes = 0;
   CHECK_CUDA_ERROR(cudaGraphGetNodes(graph, nullptr, &num_nodes));
   if (num_nodes == 0) {
-    return true;
+    return {key + ")", true};
   }
-
+  bool is_updatable = true;
   std::vector<cudaGraphNode_t> nodes(num_nodes);
   CHECK_CUDA_ERROR(cudaGraphGetNodes(graph, nodes.data(), &num_nodes));
   for (const auto& node : nodes) {
+    if (!is_updatable) {
+      break;
+    }
     cudaGraphNodeType type;
     CHECK_CUDA_ERROR(cudaGraphNodeGetType(node, &type));
-    if (type == cudaGraphNodeTypeGraph) {
+    switch (type) {
+      case cudaGraphNodeTypeGraph: {
         // Try to be updatable for a structure like graph -> graph -> kernel
-      if (num_nodes > 1) {
-        return false;
-      }
         cudaGraph_t child;
         CHECK_CUDA_ERROR(cudaGraphChildGraphNodeGetGraph(node, &child));
-      return is_graph_updatable(child, cluster_dim_x);
+        auto [subkey, sub_is_updatable] = subgraph_to_key(child);
-    } else if (type != cudaGraphNodeTypeKernel) {
+        is_updatable &= sub_is_updatable;
-      return false;
+        key += subkey;
-    } else {
+        break;
+      }
+      case cudaGraphNodeTypeMemset:
+        key += "M";
+        break;
+      case cudaGraphNodeTypeKernel: {
         cudaLaunchAttributeValue cluster_dim;
         CHECK_CUDA_ERROR(cudaGraphKernelNodeGetAttribute(
             node, cudaLaunchAttributeClusterDimension, &cluster_dim));
-      // Only dim.x can be greater than 1
+        // Only allow dim.x to be greater than 1
         if (cluster_dim.clusterDim.y > 1 || cluster_dim.clusterDim.z > 1) {
-        return false;
+          is_updatable = false;
+        } else {
+          key += "K";
+          key += std::to_string(cluster_dim.clusterDim.x);
         }
-      // Only one child node allowed when subgraph uses clusters
+        break;
-      if (cluster_dim.clusterDim.x > 0 && num_nodes > 1) {
-        return false;
       }
-      cluster_dim_x = cluster_dim.clusterDim.x;
+      case cudaGraphNodeTypeWaitEvent:
+        key += "W";
+        break;
+      case cudaGraphNodeTypeEventRecord:
+        key += "R";
+        break;
+      default:
+        is_updatable = false;
     }
   }
-  return true;
+  key += ")";
+  return {key, is_updatable};
 }
 
 void CommandEncoder::add_graph_node(cudaGraph_t child) {
@@ -370,11 +388,10 @@ void CommandEncoder::add_graph_node(cudaGraph_t child) {
     return;
   }
   cudaGraphNode_t node;
-  int cluster_dim_x = 0;
+  auto [sub_graph_key, is_updatable] = subgraph_to_key(child);
-  is_graph_updatable_ &= is_graph_updatable(child, cluster_dim_x);
+  is_graph_updatable_ &= is_updatable;
   CHECK_CUDA_ERROR(cudaGraphAddChildGraphNode(&node, graph_, NULL, 0, child));
-  insert_graph_dependencies(
+  insert_graph_dependencies(GraphNode{node, sub_graph_key});
-      GraphNode{node, "G" + std::to_string(cluster_dim_x)});
 }
 
 bool CommandEncoder::needs_commit() {

mlx/backend/cuda/device.h

@@ -106,7 +106,7 @@ class CommandEncoder {
     cudaGraphNode_t node;
     // K = kernel
     // E = empty
-    // G* = subgraph (with metadata)
+    // () = subgraph (with metadata)
     // Symbols ':', '-' are reserved as separators
     std::string node_type;
     std::string id;

mlx/backend/cuda/reduce/col_reduce.cu

@@ -89,9 +89,13 @@ template <
     int NDIM,
     int BM,
     int BN,
-    int N_READS = 4>
+    int N_READS = 4,
-__global__ void
+    int BLOCKS = 1>
-col_reduce_looped(T* in, U* out, const __grid_constant__ ColReduceArgs args) {
+__global__ void col_reduce_looped(
+    T* in,
+    U* out,
+    const __grid_constant__ ColReduceArgs args,
+    int64_t out_size) {
   auto grid = cg::this_grid();
   auto block = cg::this_thread_block();
   auto warp = cg::tiled_partition<WARP_SIZE>(block);
@@ -102,6 +106,8 @@ col_reduce_looped(T* in, U* out, const __grid_constant__ ColReduceArgs args) {
   size_t tile_idx = grid.block_rank();
   size_t tile_x = tile_idx % ((args.reduction_stride + BN - 1) / BN);
   size_t tile_y = tile_idx / ((args.reduction_stride + BN - 1) / BN);
+  size_t tile_out = tile_y / out_size;
+  tile_y = tile_y % out_size;
 
   // Compute the indices for the thread within the tile
   short thread_x = block.thread_rank() % threads_per_row;
@@ -118,12 +124,23 @@ col_reduce_looped(T* in, U* out, const __grid_constant__ ColReduceArgs args) {
     totals[i] = ReduceInit<Op, T>::value();
   }
 
-  LoopedElemToLoc<NDIM, (NDIM > 2)> loop(args.reduce_ndim);
-  loop.next(thread_y, args.reduce_shape.data(), args.reduce_strides.data());
   size_t total = args.non_col_reductions * args.reduction_size;
+  size_t per_block, start, end;
+  if constexpr (BLOCKS > 1) {
+    per_block = (total + BLOCKS - 1) / BLOCKS;
+    start = tile_out * per_block + thread_y;
+    end = min((tile_out + 1) * per_block, total);
+  } else {
+    per_block = total;
+    start = thread_y;
+    end = total;
+  }
+
+  LoopedElemToLoc<NDIM, (NDIM > 2)> loop(args.reduce_ndim);
+  loop.next(start, args.reduce_shape.data(), args.reduce_strides.data());
   if (tile_x * BN + BN <= args.reduction_stride) {
     if (args.reduction_stride % N_READS == 0) {
-      for (size_t r = thread_y; r < total; r += BM) {
+      for (size_t r = start; r < end; r += BM) {
         T vals[N_READS];
         cub::LoadDirectBlockedVectorized(thread_x, in + loop.location(), vals);
         for (int i = 0; i < N_READS; i++) {
@@ -132,7 +149,7 @@ col_reduce_looped(T* in, U* out, const __grid_constant__ ColReduceArgs args) {
         loop.next(BM, args.reduce_shape.data(), args.reduce_strides.data());
       }
     } else {
-      for (size_t r = thread_y; r < total; r += BM) {
+      for (size_t r = start; r < end; r += BM) {
         T vals[N_READS];
         cub::LoadDirectBlocked(thread_x, in + loop.location(), vals);
         for (int i = 0; i < N_READS; i++) {
@@ -142,7 +159,7 @@ col_reduce_looped(T* in, U* out, const __grid_constant__ ColReduceArgs args) {
       }
     }
   } else {
-    for (size_t r = thread_y; r < total; r += BM) {
+    for (size_t r = start; r < end; r += BM) {
       T vals[N_READS];
       cub::LoadDirectBlocked(
           thread_x,
@@ -173,6 +190,9 @@ col_reduce_looped(T* in, U* out, const __grid_constant__ ColReduceArgs args) {
 
   // Write result.
   if (warp.thread_rank() == 0) {
+    if (BLOCKS > 1) {
+      out += tile_out * out_size * args.reduction_stride;
+    }
     cub::StoreDirectBlocked(
         warp.meta_group_rank(),
         out + tile_y * args.reduction_stride + tile_x * BN,
@@ -227,11 +247,12 @@ __global__ void col_reduce_small(
 inline auto output_grid_for_col_reduce(
     const array& out,
     const cu::ColReduceArgs& args,
-    int bn) {
+    int bn,
+    int outer = 1) {
   int gx, gy = 1;
   size_t n_inner_blocks = cuda::ceil_div(args.reduction_stride, bn);
   size_t n_outer_blocks = out.size() / args.reduction_stride;
-  size_t n_blocks = n_outer_blocks * n_inner_blocks;
+  size_t n_blocks = n_outer_blocks * n_inner_blocks * outer;
   while (n_blocks / gy > INT32_MAX) {
     gy *= 2;
   }
@@ -277,7 +298,8 @@ void col_reduce_looped(
             0,
             indata,
             gpu_ptr<U>(out),
-            static_cast<cu::ColReduceArgs>(args));
+            static_cast<cu::ColReduceArgs>(args),
+            out.size() / args.reduction_stride);
       });
     });
   });
@@ -320,6 +342,117 @@ void col_reduce_small(
   });
 }
 
+void col_reduce_two_pass(
+    cu::CommandEncoder& encoder,
+    const array& in,
+    array& out,
+    Reduce::ReduceType reduce_type,
+    const std::vector<int>& axes,
+    const ReductionPlan& plan,
+    const cu::ColReduceArgs& args) {
+  // Allocate data for the output using in's layout to access them as
+  // contiguously as possible.
+  allocate_same_layout(out, in, axes, encoder);
+
+  // Allocate an intermediate array to hold the 1st pass result
+  constexpr int outer = 32;
+
+  Shape intermediate_shape;
+  intermediate_shape.push_back(outer);
+  intermediate_shape.insert(
+      intermediate_shape.end(), out.shape().begin(), out.shape().end());
+
+  Strides intermediate_strides;
+  intermediate_strides.push_back(out.size());
+  intermediate_strides.insert(
+      intermediate_strides.end(), out.strides().begin(), out.strides().end());
+
+  array intermediate(intermediate_shape, out.dtype(), nullptr, {});
+  auto [data_size, rc, cc] =
+      check_contiguity(intermediate_shape, intermediate_strides);
+  auto fl = out.flags();
+  fl.row_contiguous = rc;
+  fl.col_contiguous = cc;
+  fl.contiguous = true;
+  intermediate.set_data(
+      cu::malloc_async(intermediate.nbytes(), encoder),
+      data_size,
+      intermediate_strides,
+      fl,
+      allocator::free);
+
+  encoder.add_temporary(intermediate);
+  encoder.set_input_array(in);
+  encoder.set_output_array(intermediate);
+  dispatch_all_types(in.dtype(), [&](auto type_tag) {
+    dispatch_reduce_ops(reduce_type, [&](auto reduce_type_tag) {
+      dispatch_reduce_ndim(args.reduce_ndim, [&](auto reduce_ndim) {
+        using OP = MLX_GET_TYPE(reduce_type_tag);
+        using T = cuda_type_t<MLX_GET_TYPE(type_tag)>;
+        using U = typename cu::ReduceResult<OP, T>::type;
+        // Cub doesn't like const pointers for vectorized loads. (sigh)
+        T* indata = const_cast<T*>(gpu_ptr<T>(in));
+
+        constexpr int N_READS = 4;
+        constexpr int BM = 32;
+        constexpr int BN = 32;
+        dim3 grid = output_grid_for_col_reduce(out, args, BN, outer);
+        int blocks = BM * BN / N_READS;
+        auto kernel = cu::
+            col_reduce_looped<T, U, OP, reduce_ndim(), BM, BN, N_READS, outer>;
+        encoder.add_kernel_node(
+            kernel,
+            grid,
+            blocks,
+            0,
+            indata,
+            gpu_ptr<U>(intermediate),
+            static_cast<cu::ColReduceArgs>(args),
+            out.size() / args.reduction_stride);
+      });
+    });
+  });
+
+  // Prepare the reduction arguments for the 2nd pass
+  cu::ColReduceArgs second_args = args;
+  second_args.reduction_size = outer;
+  second_args.reduction_stride = out.size();
+  second_args.ndim = 0;
+  second_args.reduce_shape[0] = outer;
+  second_args.reduce_strides[0] = out.size();
+  second_args.reduce_ndim = 1;
+  second_args.non_col_reductions = 1;
+
+  encoder.set_input_array(intermediate);
+  encoder.set_output_array(out);
+  dispatch_all_types(intermediate.dtype(), [&](auto type_tag) {
+    dispatch_reduce_ops(reduce_type, [&](auto reduce_type_tag) {
+      dispatch_reduce_ndim(second_args.reduce_ndim, [&](auto reduce_ndim) {
+        using OP = MLX_GET_TYPE(reduce_type_tag);
+        using T = cuda_type_t<MLX_GET_TYPE(type_tag)>;
+        using U = typename cu::ReduceResult<OP, T>::type;
+
+        constexpr int N_READS = 4;
+        constexpr int BM = 32;
+        constexpr int BN = 32;
+        dim3 grid = output_grid_for_col_reduce(out, second_args, BN);
+        int blocks = BM * BN / N_READS;
+        auto kernel =
+            cu::col_reduce_looped<T, U, OP, reduce_ndim(), BM, BN, N_READS>;
+        encoder.add_kernel_node(
+            kernel,
+            grid,
+            blocks,
+            0,
+            gpu_ptr<T>(intermediate),
+            gpu_ptr<U>(out),
+            second_args,
+            second_args.reduction_stride);
+      });
+    });
+  });
+}
+
 void col_reduce(
     cu::CommandEncoder& encoder,
     const array& in,
@@ -334,6 +467,18 @@ void col_reduce(
   //   It is a general strided reduce. Each threadblock computes the output for
   //   a subrow of the fast moving axis. For instance 32 elements.
   //
+  // - col_reduce_small
+  //
+  //  It is a column reduce for small columns. Each thread loops over the whole
+  //  column without communicating with any other thread.
+  //
+  // - col_reduce_two_pass
+  //
+  //  It is a reduce for long columns. To increase parallelism, we split the
+  //  reduction in two passes. First we do a column reduce where many
+  //  threadblocks operate on different parts of the reduced axis. Then we
+  //  perform a final column reduce.
+  //
   // Notes: As in row reduce we opt to read as much in order as possible and
   //        leave transpositions as they are (contrary to our Metal backend).
   //
@@ -349,6 +494,14 @@ void col_reduce(
     return;
   }
 
+  // Long column with smallish row
+  size_t total_sums = args.non_col_reductions * args.reduction_size;
+  size_t approx_threads = out.size();
+  if (total_sums / approx_threads > 32) {
+    col_reduce_two_pass(encoder, in, out, reduce_type, axes, plan, args);
+    return;
+  }
+
   // Fallback col reduce
   col_reduce_looped(encoder, in, out, reduce_type, axes, plan, args);
 }

mlx/backend/cuda/utils.cpp

@@ -80,7 +80,6 @@ CudaGraph::CudaGraph(cu::Device& device) {
 }
 
 void CudaGraph::end_capture(cudaStream_t stream) {
-  assert(handle_ == nullptr);
   CHECK_CUDA_ERROR(cudaStreamEndCapture(stream, &handle_));
 }
 

mlx/backend/gpu/copy.cpp

@@ -7,8 +7,6 @@
 
 namespace mlx::core {
 
-void copy_gpu(const array& in, array& out, CopyType ctype, const Stream& s);
-
 void copy_gpu(const array& in, array& out, CopyType ctype) {
   copy_gpu(in, out, ctype, out.primitive().stream());
 }

mlx/backend/metal/allocator.cpp

@@ -149,7 +149,9 @@ Buffer MetalAllocator::malloc(size_t size) {
       buf = device_->newBuffer(size, resource_options);
     }
     if (!buf) {
-      return Buffer{nullptr};
+      std::ostringstream msg;
+      msg << "[malloc] Unable to allocate " << size << " bytes.";
+      throw std::runtime_error(msg.str());
     }
     lk.lock();
     num_resources_++;
@@ -201,6 +203,32 @@ size_t MetalAllocator::size(Buffer buffer) const {
   return static_cast<MTL::Buffer*>(buffer.ptr())->length();
 }
 
+Buffer MetalAllocator::make_buffer(void* ptr, size_t size) {
+  auto buf = device_->newBuffer(ptr, size, resource_options, nullptr);
+  if (!buf) {
+    return Buffer{nullptr};
+  }
+  std::unique_lock lk(mutex_);
+  residency_set_.insert(buf);
+  active_memory_ += buf->length();
+  peak_memory_ = std::max(peak_memory_, active_memory_);
+  num_resources_++;
+  return Buffer{static_cast<void*>(buf)};
+}
+
+void MetalAllocator::release(Buffer buffer) {
+  auto buf = static_cast<MTL::Buffer*>(buffer.ptr());
+  if (buf == nullptr) {
+    return;
+  }
+  std::unique_lock lk(mutex_);
+  active_memory_ -= buf->length();
+  num_resources_--;
+  lk.unlock();
+  auto pool = metal::new_scoped_memory_pool();
+  buf->release();
+}
+
 MetalAllocator& allocator() {
   // By creating the |allocator_| on heap, the destructor of MetalAllocator
   // will not be called on exit and buffers in the cache will be leaked. This

mlx/backend/metal/allocator.h

@@ -21,6 +21,9 @@ class MetalAllocator : public allocator::Allocator {
   virtual Buffer malloc(size_t size) override;
   virtual void free(Buffer buffer) override;
   virtual size_t size(Buffer buffer) const override;
+  virtual Buffer make_buffer(void* ptr, size_t size) override;
+  virtual void release(Buffer buffer) override;
+
   size_t get_active_memory() {
     return active_memory_;
   };

mlx/backend/no_gpu/allocator.cpp

@@ -25,6 +25,7 @@ class CommonAllocator : public Allocator {
   virtual Buffer malloc(size_t size) override;
   virtual void free(Buffer buffer) override;
   virtual size_t size(Buffer buffer) const override;
+
   size_t get_active_memory() const {
     return active_memory_;
   };

mlx/distributed/CMakeLists.txt

@@ -4,11 +4,6 @@ target_sources(
           ${CMAKE_CURRENT_SOURCE_DIR}/ops.cpp
           ${CMAKE_CURRENT_SOURCE_DIR}/distributed.cpp)
 
-if(MLX_BUILD_CPU AND NOT WIN32)
-  target_sources(mlx PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/utils.cpp)
-endif()
-
 add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/mpi)
 add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/ring)
 add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/nccl)
-add_subdirectory(${CMAKE_CURRENT_SOURCE_DIR}/jaccl)

mlx/distributed/distributed.cpp

@@ -5,7 +5,6 @@
 #include "mlx/backend/cuda/cuda.h"
 #include "mlx/distributed/distributed.h"
 #include "mlx/distributed/distributed_impl.h"
-#include "mlx/distributed/jaccl/jaccl.h"
 #include "mlx/distributed/mpi/mpi.h"
 #include "mlx/distributed/nccl/nccl.h"
 #include "mlx/distributed/ring/ring.h"
@@ -103,27 +102,7 @@ class EmptyGroup : public GroupImpl {
 } // namespace detail
 
 bool is_available() {
-  return mpi::is_available() || ring::is_available() || nccl::is_available() ||
+  return mpi::is_available() || ring::is_available() || nccl::is_available();
-      jaccl::is_available();
-}
-
-bool is_available(const std::string& bk) {
-  if (bk == "any") {
-    return is_available();
-  }
-  if (bk == "mpi") {
-    return mpi::is_available();
-  }
-  if (bk == "ring") {
-    return ring::is_available();
-  }
-  if (bk == "nccl") {
-    return nccl::is_available();
-  }
-  if (bk == "jaccl") {
-    return jaccl::is_available();
-  }
-  return false;
 }
 
 int Group::rank() const {
@@ -156,8 +135,6 @@ Group init(bool strict /* = false */, const std::string& bk /* = "any" */) {
     group = ring::init(strict);
   } else if (bk == "nccl") {
     group = nccl::init(strict);
-  } else if (bk == "jaccl") {
-    group = jaccl::init(strict);
   } else if (bk == "any") {
     if (mlx::core::cu::is_available()) {
       group = nccl::init(false);
@@ -171,17 +148,13 @@ Group init(bool strict /* = false */, const std::string& bk /* = "any" */) {
       group = mpi::init(false);
       bk_ = "mpi";
     }
-    if (group == nullptr) {
-      group = jaccl::init(false);
-      bk_ = "jaccl";
-    }
     if (group == nullptr && strict) {
       throw std::runtime_error("[distributed] Couldn't initialize any backend");
     }
   } else {
     std::ostringstream msg;
-    msg << "[distributed] The only valid values for backend are 'any', 'mpi', 'nccl', "
+    msg << "[distributed] The only valid values for backend are 'any', 'mpi' "
-        << "'jaccl' and 'ring' but '" << bk << "' was provided.";
+        << "and 'ring' but '" << bk << "' was provided.";
     throw std::invalid_argument(msg.str());
   }
 

mlx/distributed/distributed.h

@@ -16,7 +16,6 @@ class GroupImpl;
 
 /* Check if a communication backend is available */
 bool is_available();
-bool is_available(const std::string& bk);
 
 /**
  * A distributed::Group represents a group of independent mlx processes that

mlx/distributed/jaccl/CMakeLists.txt

@@ -1,8 +0,0 @@
-if(MLX_BUILD_CPU
-   AND ${CMAKE_SYSTEM_NAME} MATCHES "Darwin"
-   AND MACOS_SDK_VERSION GREATER_EQUAL 26.2)
-  target_sources(mlx PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/jaccl.cpp)
-  target_link_libraries(mlx PRIVATE rdma)
-else()
-  target_sources(mlx PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/no_jaccl.cpp)
-endif()

mlx/distributed/jaccl/jaccl.h

@@ -1,12 +0,0 @@
-// Copyright © 2025 Apple Inc.
-
-#include "mlx/distributed/distributed.h"
-
-namespace mlx::core::distributed::jaccl {
-
-using GroupImpl = mlx::core::distributed::detail::GroupImpl;
-
-bool is_available();
-std::shared_ptr<GroupImpl> init(bool strict = false);
-
-} // namespace mlx::core::distributed::jaccl

mlx/distributed/jaccl/no_jaccl.cpp

@@ -1,20 +0,0 @@
-// Copyright © 2025 Apple Inc.
-
-#include "mlx/distributed/jaccl/jaccl.h"
-
-namespace mlx::core::distributed::jaccl {
-
-using GroupImpl = mlx::core::distributed::detail::GroupImpl;
-
-bool is_available() {
-  return false;
-}
-
-std::shared_ptr<GroupImpl> init(bool strict /* = false */) {
-  if (strict) {
-    throw std::runtime_error("Cannot initialize jaccl distributed backend.");
-  }
-  return nullptr;
-}
-
-} // namespace mlx::core::distributed::jaccl

mlx/distributed/reduction_ops.h

@@ -1,38 +0,0 @@
-// Copyright © 2025 Apple Inc.
-
-namespace mlx::core::distributed::detail {
-
-template <typename T>
-struct SumOp {
-  void operator()(const T* input, T* output, size_t N) const {
-    while (N-- > 0) {
-      *output += *input;
-      input++;
-      output++;
-    }
-  }
-};
-
-template <typename T>
-struct MaxOp {
-  void operator()(const T* input, T* output, size_t N) const {
-    while (N-- > 0) {
-      *output = std::max(*output, *input);
-      input++;
-      output++;
-    }
-  }
-};
-
-template <typename T>
-struct MinOp {
-  void operator()(const T* input, T* output, size_t N) const {
-    while (N-- > 0) {
-      *output = std::min(*output, *input);
-      input++;
-      output++;
-    }
-  }
-};
-
-} // namespace mlx::core::distributed::detail

mlx/distributed/ring/ring.cpp

@@ -1,6 +1,9 @@
 // Copyright © 2024 Apple Inc.
 
+#include <arpa/inet.h>
 #include <fcntl.h>
+#include <netdb.h>
+#include <netinet/in.h>
 #include <netinet/tcp.h>
 #include <sys/socket.h>
 #include <unistd.h>
@@ -19,8 +22,6 @@
 #include "mlx/backend/cpu/encoder.h"
 #include "mlx/distributed/distributed.h"
 #include "mlx/distributed/distributed_impl.h"
-#include "mlx/distributed/reduction_ops.h"
-#include "mlx/distributed/utils.h"
 #include "mlx/threadpool.h"
 
 #ifndef SOL_TCP
@@ -93,7 +94,6 @@ constexpr const size_t ALL_SUM_SIZE = 8 * 1024 * 1024;
 constexpr const size_t ALL_SUM_BUFFERS = 2;
 constexpr const int CONN_ATTEMPTS = 5;
 constexpr const int CONN_WAIT = 1000;
-constexpr const char* RING_TAG = "[ring]";
 
 using GroupImpl = mlx::core::distributed::detail::GroupImpl;
 using json = nlohmann::json;
@@ -296,6 +296,55 @@ class CommunicationThreads {
   std::unordered_map<int, SocketThread> threads_;
 };
 
+struct address_t {
+  sockaddr_storage addr;
+  socklen_t len;
+
+  const sockaddr* get() const {
+    return (struct sockaddr*)&addr;
+  }
+};
+
+/**
+ * Parse a sockaddr from an ip and port provided as strings.
+ */
+address_t parse_address(const std::string& ip, const std::string& port) {
+  struct addrinfo hints, *res;
+  memset(&hints, 0, sizeof(hints));
+  hints.ai_family = AF_UNSPEC;
+  hints.ai_socktype = SOCK_STREAM;
+
+  int status = getaddrinfo(ip.c_str(), port.c_str(), &hints, &res);
+  if (status != 0) {
+    std::ostringstream msg;
+    msg << "Can't parse address " << ip << ":" << port;
+    throw std::runtime_error(msg.str());
+  }
+
+  address_t result;
+  memcpy(&result.addr, res->ai_addr, res->ai_addrlen);
+  result.len = res->ai_addrlen;
+  freeaddrinfo(res);
+
+  return result;
+}
+
+/**
+ * Parse a sockaddr provided as an <ip>:<port> string.
+ */
+address_t parse_address(const std::string& ip_port) {
+  auto colon = ip_port.find(":");
+  if (colon == std::string::npos) {
+    std::ostringstream msg;
+    msg << "Can't parse address " << ip_port;
+    throw std::runtime_error(msg.str());
+  }
+  std::string ip(ip_port.begin(), ip_port.begin() + colon);
+  std::string port(ip_port.begin() + colon + 1, ip_port.end());
+
+  return parse_address(ip, port);
+}
+
 /**
  * Load all addresses from the json hostfile. The hostfile is a list of
  * addresses in order of rank. For each rank there can be many addresses so
@@ -308,15 +357,15 @@ class CommunicationThreads {
  *    ["ip3:5000", "ip3:5001"],
  *  ]
  */
-std::vector<std::vector<detail::address_t>> load_nodes(const char* hostfile) {
+std::vector<std::vector<address_t>> load_nodes(const char* hostfile) {
-  std::vector<std::vector<detail::address_t>> nodes;
+  std::vector<std::vector<address_t>> nodes;
   std::ifstream f(hostfile);
 
   json hosts = json::parse(f);
   for (auto& h : hosts) {
-    std::vector<detail::address_t> host;
+    std::vector<address_t> host;
     for (auto& ips : h) {
-      host.push_back(std::move(detail::parse_address(ips.get<std::string>())));
+      host.push_back(parse_address(ips.get<std::string>()));
     }
     nodes.push_back(std::move(host));
   }
@@ -328,15 +377,73 @@ std::vector<std::vector<detail::address_t>> load_nodes(const char* hostfile) {
  * Create a socket and accept one connection for each of the provided
  * addresses.
  */
-std::vector<int> accept_connections(
+std::vector<int> accept_connections(const std::vector<address_t>& addresses) {
-    const std::vector<detail::address_t>& addresses) {
   std::vector<int> sockets;
   int success;
 
   for (auto& address : addresses) {
-    detail::TCPSocket socket(RING_TAG);
+    // Create the socket to wait for connections from the peers
-    socket.listen(RING_TAG, address);
+    int sock = socket(AF_INET, SOCK_STREAM, 0);
-    sockets.push_back(socket.accept(RING_TAG).detach());
+    if (sock < 0) {
+      std::ostringstream msg;
+      msg << "[ring] Couldn't create socket (error: " << errno << ")";
+      throw std::runtime_error(msg.str());
+    }
+
+    // Make sure we can launch immediately after shutdown by setting the
+    // reuseaddr option so that we don't get address already in use errors
+    int enable = 1;
+    success = setsockopt(sock, SOL_SOCKET, SO_REUSEADDR, &enable, sizeof(int));
+    if (success < 0) {
+      shutdown(sock, 2);
+      close(sock);
+      std::ostringstream msg;
+      msg << "[ring] Couldn't enable reuseaddr (error: " << errno << ")";
+      throw std::runtime_error(msg.str());
+    }
+    success = setsockopt(sock, SOL_SOCKET, SO_REUSEPORT, &enable, sizeof(int));
+    if (success < 0) {
+      shutdown(sock, 2);
+      close(sock);
+      std::ostringstream msg;
+      msg << "[ring] Couldn't enable reuseport (error: " << errno << ")";
+      throw std::runtime_error(msg.str());
+    }
+
+    // Bind the socket to the address and port
+    success = bind(sock, address.get(), address.len);
+    if (success < 0) {
+      shutdown(sock, 2);
+      close(sock);
+      std::ostringstream msg;
+      msg << "[ring] Couldn't bind socket (error: " << errno << ")";
+      throw std::runtime_error(msg.str());
+    }
+
+    // Wait for connections
+    success = listen(sock, 0);
+    if (success < 0) {
+      shutdown(sock, 2);
+      close(sock);
+      std::ostringstream msg;
+      msg << "[ring] Couldn't listen (error: " << errno << ")";
+      throw std::runtime_error(msg.str());
+    }
+
+    int peer_socket = accept(sock, nullptr, nullptr);
+    if (peer_socket < 0) {
+      shutdown(sock, 2);
+      close(sock);
+      std::ostringstream msg;
+      msg << "[ring] Accept failed (error: " << errno << ")";
+      throw std::runtime_error(msg.str());
+    }
+
+    // Close the listening socket
+    shutdown(sock, 2);
+    close(sock);
+
+    sockets.push_back(peer_socket);
   }
 
   return sockets;
@@ -347,42 +454,93 @@ std::vector<int> accept_connections(
  * provided addresses.
  */
 std::vector<int> make_connections(
-    const std::vector<detail::address_t>& addresses,
+    const std::vector<address_t>& addresses,
     bool verbose) {
   std::vector<int> sockets;
   int success;
 
   for (auto& address : addresses) {
-    sockets.push_back(detail::TCPSocket::connect(
+    int sock;
-                          RING_TAG,
+
-                          address,
+    // Attempt to connect to the peer CONN_ATTEMPTS times with exponential
-                          CONN_ATTEMPTS,
+    // backoff. TODO: Do we need that?
-                          CONN_WAIT,
+    for (int attempt = 0; attempt < CONN_ATTEMPTS; attempt++) {
-                          [verbose](int attempt, int wait) {
+      // Create the socket
+      sock = socket(AF_INET, SOCK_STREAM, 0);
+      if (sock < 0) {
+        std::ostringstream msg;
+        msg << "[ring] Couldn't create socket (error: " << errno << ")";
+        throw std::runtime_error(msg.str());
+      }
+
+      if (attempt > 0) {
+        int wait = (1 << (attempt - 1)) * CONN_WAIT;
         log_info(
             verbose,
             "Attempt",
             attempt,
-                                "waiting",
+            "wait",
             wait,
             "ms (error:",
             errno,
             ")");
-                          })
+        std::this_thread::sleep_for(std::chrono::milliseconds(wait));
-                          .detach());
+      }
+
+      success = connect(sock, address.get(), address.len);
+      if (success == 0) {
+        break;
+      }
+    }
+    if (success < 0) {
+      std::ostringstream msg;
+      msg << "[ring] Couldn't connect (error: " << errno << ")";
+      throw std::runtime_error(msg.str());
+    }
+
+    sockets.push_back(sock);
   }
 
   return sockets;
 }
+template <typename T>
+struct SumOp {
+  void operator()(const T* input, T* output, size_t N) {
+    while (N-- > 0) {
+      *output += *input;
+      input++;
+      output++;
+    }
+  }
+};
+
+template <typename T>
+struct MaxOp {
+  void operator()(const T* input, T* output, size_t N) {
+    while (N-- > 0) {
+      *output = std::max(*output, *input);
+      input++;
+      output++;
+    }
+  }
+};
+
+template <typename T>
+struct MinOp {
+  void operator()(const T* input, T* output, size_t N) {
+    while (N-- > 0) {
+      *output = std::min(*output, *input);
+      input++;
+      output++;
+    }
+  }
+};
 
 } // namespace
 
 class RingGroup : public GroupImpl {
  public:
-  RingGroup(
+  RingGroup(int rank, std::vector<std::vector<address_t>> nodes, bool verbose)
-      int rank,
-      std::vector<std::vector<detail::address_t>> nodes,
-      bool verbose)
       : rank_(rank), verbose_(verbose), pool_(0) {
     if (rank_ > 0 && rank_ >= nodes.size()) {
       throw std::runtime_error(
@@ -475,17 +633,17 @@ class RingGroup : public GroupImpl {
 
   void all_sum(const array& input, array& output, Stream stream) override {
     SWITCH_TYPE(
-        output, all_reduce<T>(input, output, stream, detail::SumOp<T>()));
+        output, all_reduce<T, SumOp<T>>(input, output, stream, SumOp<T>()));
   }
 
   void all_max(const array& input, array& output, Stream stream) override {
     SWITCH_TYPE(
-        output, all_reduce<T>(input, output, stream, detail::MaxOp<T>()));
+        output, all_reduce<T, MaxOp<T>>(input, output, stream, MaxOp<T>()));
   }
 
   void all_min(const array& input, array& output, Stream stream) override {
     SWITCH_TYPE(
-        output, all_reduce<T>(input, output, stream, detail::MinOp<T>()));
+        output, all_reduce<T, MinOp<T>>(input, output, stream, MinOp<T>()));
   }
 
   std::shared_ptr<GroupImpl> split(int color, int key = -1) override {

mlx/distributed/utils.cpp

@@ -1,204 +0,0 @@
-// Copyright © 2025 Apple Inc.
-
-#include <netdb.h>
-#include <unistd.h>
-#include <cstring>
-#include <sstream>
-#include <thread>
-
-#include "mlx/distributed/utils.h"
-
-namespace mlx::core::distributed::detail {
-
-/**
- * Parse a sockaddr from an ip and port provided as strings.
- */
-address_t parse_address(const std::string& ip, const std::string& port) {
-  struct addrinfo hints, *res;
-  std::memset(&hints, 0, sizeof(hints));
-  hints.ai_family = AF_UNSPEC;
-  hints.ai_socktype = SOCK_STREAM;
-
-  int status = getaddrinfo(ip.c_str(), port.c_str(), &hints, &res);
-  if (status != 0) {
-    std::ostringstream msg;
-    msg << "Can't parse address " << ip << ":" << port;
-    throw std::runtime_error(msg.str());
-  }
-
-  address_t result;
-  memcpy(&result.addr, res->ai_addr, res->ai_addrlen);
-  result.len = res->ai_addrlen;
-  freeaddrinfo(res);
-
-  return result;
-}
-
-/**
- * Parse a sockaddr provided as an <ip>:<port> string.
- */
-address_t parse_address(const std::string& ip_port) {
-  auto colon = ip_port.find(":");
-  if (colon == std::string::npos) {
-    std::ostringstream msg;
-    msg << "Can't parse address " << ip_port;
-    throw std::runtime_error(msg.str());
-  }
-  std::string ip(ip_port.begin(), ip_port.begin() + colon);
-  std::string port(ip_port.begin() + colon + 1, ip_port.end());
-
-  return parse_address(ip, port);
-}
-
-TCPSocket::TCPSocket(const char* tag) {
-  sock_ = socket(AF_INET, SOCK_STREAM, 0);
-  if (sock_ < 0) {
-    std::ostringstream msg;
-    msg << tag << " Couldn't create socket (error: " << errno << ")";
-    throw std::runtime_error(msg.str());
-  }
-}
-
-TCPSocket::TCPSocket(TCPSocket&& s) {
-  sock_ = s.sock_;
-  s.sock_ = -1;
-}
-
-TCPSocket& TCPSocket::operator=(TCPSocket&& s) {
-  if (this != &s) {
-    sock_ = s.sock_;
-    s.sock_ = -1;
-  }
-  return *this;
-}
-
-TCPSocket::TCPSocket(int s) : sock_(s) {}
-
-TCPSocket::~TCPSocket() {
-  if (sock_ > 0) {
-    shutdown(sock_, 2);
-    close(sock_);
-  }
-}
-
-int TCPSocket::detach() {
-  int s = sock_;
-  sock_ = -1;
-  return s;
-}
-
-void TCPSocket::listen(const char* tag, const address_t& addr) {
-  int success;
-
-  // Make sure we can launch immediately after shutdown by setting the
-  // reuseaddr option so that we don't get address already in use errors
-  int enable = 1;
-  success = setsockopt(sock_, SOL_SOCKET, SO_REUSEADDR, &enable, sizeof(int));
-  if (success < 0) {
-    std::ostringstream msg;
-    msg << tag << " Couldn't enable reuseaddr (error: " << errno << ")";
-    throw std::runtime_error(msg.str());
-  }
-  success = setsockopt(sock_, SOL_SOCKET, SO_REUSEPORT, &enable, sizeof(int));
-  if (success < 0) {
-    std::ostringstream msg;
-    msg << tag << " Couldn't enable reuseport (error: " << errno << ")";
-    throw std::runtime_error(msg.str());
-  }
-
-  // Bind the socket to the address and port
-  success = bind(sock_, addr.get(), addr.len);
-  if (success < 0) {
-    std::ostringstream msg;
-    msg << tag << " Couldn't bind socket (error: " << errno << ")";
-    throw std::runtime_error(msg.str());
-  }
-
-  // Prepare waiting for connections
-  success = ::listen(sock_, 0);
-  if (success < 0) {
-    std::ostringstream msg;
-    msg << tag << " Couldn't listen (error: " << errno << ")";
-    throw std::runtime_error(msg.str());
-  }
-}
-
-TCPSocket TCPSocket::accept(const char* tag) {
-  int peer = ::accept(sock_, nullptr, nullptr);
-  if (peer < 0) {
-    std::ostringstream msg;
-    msg << tag << " Accept failed (error: " << errno << ")";
-    throw std::runtime_error(msg.str());
-  }
-
-  return TCPSocket(peer);
-}
-
-void TCPSocket::send(const char* tag, const void* data, size_t len) {
-  while (len > 0) {
-    auto n = ::send(sock_, data, len, 0);
-    if (n <= 0) {
-      std::ostringstream msg;
-      msg << tag << " Send failed with errno=" << errno;
-      throw std::runtime_error(msg.str());
-    }
-    len -= n;
-    data = static_cast<const char*>(data) + n;
-  }
-}
-
-void TCPSocket::recv(const char* tag, void* data, size_t len) {
-  while (len > 0) {
-    auto n = ::recv(sock_, data, len, 0);
-    if (n <= 0) {
-      std::ostringstream msg;
-      msg << tag << " Recv failed with errno=" << errno;
-      throw std::runtime_error(msg.str());
-    }
-    len -= n;
-    data = static_cast<char*>(data) + n;
-  }
-}
-
-TCPSocket TCPSocket::connect(
-    const char* tag,
-    const address_t& addr,
-    int num_retries,
-    int wait,
-    std::function<void(int, int)> cb) {
-  int sock, success;
-
-  // Attempt to connect `num_retries` times with exponential backoff.
-  for (int attempt = 0; attempt < num_retries; attempt++) {
-    // Create the socket
-    sock = socket(AF_INET, SOCK_STREAM, 0);
-    if (sock < 0) {
-      std::ostringstream msg;
-      msg << tag << " Couldn't create socket to connect (error: " << errno
-          << ")";
-      throw std::runtime_error(msg.str());
-    }
-
-    success = ::connect(sock, addr.get(), addr.len);
-    if (success == 0) {
-      break;
-    }
-
-    cb(attempt, wait);
-    if (wait > 0) {
-      std::this_thread::sleep_for(std::chrono::milliseconds(wait));
-    }
-
-    wait <<= 1;
-  }
-
-  if (success < 0) {
-    std::ostringstream msg;
-    msg << tag << " Couldn't connect (error: " << errno << ")";
-    throw std::runtime_error(msg.str());
-  }
-
-  return TCPSocket(sock);
-}
-
-} // namespace mlx::core::distributed::detail

mlx/distributed/utils.h

@@ -1,67 +0,0 @@
-// Copyright © 2025 Apple Inc.
-
-#pragma once
-
-#include <sys/socket.h>
-#include <functional>
-#include <string>
-
-namespace mlx::core::distributed::detail {
-
-struct address_t {
-  sockaddr_storage addr;
-  socklen_t len;
-
-  const sockaddr* get() const {
-    return (struct sockaddr*)&addr;
-  }
-};
-
-/**
- * Parse a sockaddr from an ip and port provided as strings.
- */
-address_t parse_address(const std::string& ip, const std::string& port);
-
-/**
- * Parse a sockaddr provided as an <ip>:<port> string.
- */
-address_t parse_address(const std::string& ip_port);
-
-/**
- * Small wrapper over a TCP socket to simplify initiating connections.
- */
-class TCPSocket {
- public:
-  TCPSocket(const char* tag);
-  TCPSocket(const TCPSocket&) = delete;
-  TCPSocket& operator=(const TCPSocket&) = delete;
-  TCPSocket(TCPSocket&& s);
-  TCPSocket& operator=(TCPSocket&&);
-  ~TCPSocket();
-
-  void listen(const char* tag, const address_t& addr);
-  TCPSocket accept(const char* tag);
-
-  void send(const char* tag, const void* data, size_t len);
-  void recv(const char* tag, void* data, size_t len);
-
-  int detach();
-
-  operator int() const {
-    return sock_;
-  }
-
-  static TCPSocket connect(
-      const char* tag,
-      const address_t& addr,
-      int num_retries = 1,
-      int wait = 0,
-      std::function<void(int, int)> cb = nullptr);
-
- private:
-  TCPSocket(int sock);
-
-  int sock_;
-};
-
-} // namespace mlx::core::distributed::detail

python/mlx/_distributed_utils/common.py

@@ -1,85 +0,0 @@
-# Copyright © 2025 Apple Inc.
-
-import ipaddress
-import json
-import sys
-from dataclasses import dataclass
-from pathlib import Path
-from typing import Optional
-
-
-@dataclass
-class Host:
-    rank: int
-    ssh_hostname: str
-    ips: list[str]
-    rdma: list[Optional[str]]
-
-
-def positive_number(x):
-    x = int(x)
-    if x <= 0:
-        raise ValueError("Number should be positive")
-    return x
-
-
-def log(verbose, *args, **kwargs):
-    if not verbose:
-        return
-    print("\033[32m[INFO]", *args, "\033[0m", **kwargs)
-
-
-def log_warning(*args, **kwargs):
-    kwargs["file"] = sys.stderr
-    print("\033[33m[WARN]", *args, "\033[0m", **kwargs)
-
-
-def log_error(*args, **kwargs):
-    kwargs["file"] = sys.stderr
-    print("\033[31m[ERROR]", *args, "\033[0m", **kwargs)
-
-
-def parse_hostlist(parser, hostlist, repeats):
-    hosts = []
-    for i, h in enumerate(hostlist.split(",")):
-        if h == "":
-            raise ValueError("Hostname cannot be empty")
-        try:
-            ipaddress.ip_address(h)
-            ips = [h]
-        except ValueError:
-            ips = []
-        for i in range(repeats):
-            hosts.append(Host(i, h, ips))
-    return hosts
-
-
-def parse_hostfile(parser, hostfile):
-    """Parse the json hostfile that contains both the hostnames to ssh into and
-    the ips to communicate over when using the ring backend.
-
-    Example:
-
-        [
-            {"ssh": "hostname1", "ips": ["123.123.123.1"], "rdma": [null, "rdma_en2", "rdma_en3"]},
-            {"ssh": "hostname2", "ips": ["123.123.123.2"], "rdma": ["rdma_en2", null, "rdma_en3"]},
-            ...
-            {"ssh": "hostnameN", "ips": ["123.123.123.N"], "rdma": ["rdma_en2", "rdma_en3", null]},
-        ]
-
-    Args:
-        hostfile (str): The path to the json file containing the host
-            information
-    """
-    hostfile = Path(hostfile)
-    if not hostfile.exists():
-        parser.error(f"Hostfile {str(hostfile)} doesn't exist")
-
-    try:
-        hosts = []
-        with open(hostfile) as f:
-            for i, h in enumerate(json.load(f)):
-                hosts.append(Host(i, h["ssh"], h.get("ips", []), h.get("rdma", [])))
-        return hosts
-    except Exception as e:
-        parser.error(f"Failed to parse hostfile {str(hostfile)} ({str(e)})")

python/mlx/_distributed_utils/launch.py

@@ -1,540 +0,0 @@
-# Copyright © 2025 Apple Inc.
-
-import argparse
-import base64
-import json
-import os
-import shlex
-import shutil
-import sys
-import tempfile
-import threading
-from collections import Counter
-from itertools import chain
-from pathlib import Path
-from queue import Empty as QueueEmpty
-from queue import Queue
-from select import select
-from subprocess import PIPE, Popen, run
-
-import mlx.core as mx
-
-from .common import log, log_warning, parse_hostfile, parse_hostlist, positive_number
-
-
-class CommandProcess:
-    @property
-    def process(self):
-        """Return the Popen object that refers to the current command."""
-        raise NotImplementedError()
-
-    @property
-    def exit_status(self):
-        """Return a tuple (returncode, killed) for the command. It should be
-        (None, None) while the command is running normally."""
-        raise NotImplementedError()
-
-    def preprocess_output(self, data: str, is_stdout=False):
-        """Preprocess the output of the command so that extra data can be
-        capture or the format changed on the fly."""
-        raise NotImplementedError()
-
-    def terminate(self):
-        """Terminate or return the exit code."""
-        raise NotImplementedError()
-
-
-class RemoteProcess(CommandProcess):
-    def __init__(self, rank, host, cwd, files, env, command):
-        is_local = host == "127.0.0.1"
-        script = RemoteProcess.make_monitor_script(rank, cwd, files, env, command)
-        script_b64 = base64.b64encode(script.encode()).decode()
-        cmd = f'{sys.executable} -c "import base64; exec(base64.b64decode(\\"{script_b64}\\"));"'
-        if not is_local:
-            cmd = f"ssh {host} '{cmd}'"
-
-        self._host = host
-        self._pidfile = None
-        self._is_local = is_local
-        self._process = Popen(
-            cmd,
-            shell=True,
-            stdin=PIPE,
-            stdout=PIPE,
-            stderr=PIPE,
-        )
-
-        self._killed = False
-
-    @property
-    def process(self):
-        return self._process
-
-    @property
-    def exit_status(self):
-        return self._process.poll(), self._killed
-
-    def preprocess_output(self, data, is_stdout=False):
-        if self._pidfile is None:
-            pidfile, *rest = data.split("\n", maxsplit=1)
-            self._pidfile = pidfile
-            return rest[0] if rest else ""
-
-        return data
-
-    def terminate(self):
-        if self._killed:
-            return
-
-        self._process.terminate()
-        self._process.wait()
-
-        # Kill the remote program if possible
-        cmd = ""
-        cmd += f"pid=$(cat {self._pidfile}); "
-        cmd += "if ps -p $pid >/dev/null; then "
-        cmd += "    kill $pid; "
-        cmd += "    echo 1; "
-        cmd += "else "
-        cmd += "    echo 0; "
-        cmd += "fi; "
-        cmd += f"rm {self._pidfile}"
-        if not self._is_local:
-            cmd = f"ssh {self._host} '{cmd}'"
-        c = run(cmd, check=True, shell=True, capture_output=True, text=True)
-
-        self._killed = c.stdout.strip() == "1"
-
-    @staticmethod
-    def make_monitor_script(rank, cwd, files, env, command):
-        # Imports that are used throughout
-        script = ""
-        script += "import os\n"
-        script += "import sys\n"
-        script += "import tempfile\n"
-        script += "from pathlib import Path\n"
-
-        # Write the PID to a file so we can kill the process if needed
-        script += "_, pidfile = tempfile.mkstemp() \n"
-        script += "open(pidfile, 'w').write(str(os.getpid()))\n"
-        script += "print(pidfile, flush=True)\n"
-
-        # Change the working directory if one was requested. Otherwise attempt to
-        # change to the current one but don't fail if it wasn't possible.
-        d = cwd or os.getcwd()
-        script += f"if Path({repr(d)}).exists():\n"
-        script += f"    os.chdir({repr(d)})\n"
-        if cwd is not None:
-            script += "else:\n"
-            script += f"    print('Failed to change directory to', {repr(d)}, file=sys.stderr)\n"
-            script += f"    sys.exit(1)\n"
-
-        # Add the environment variables that were requested
-        script += "env = dict(os.environ)\n"
-        for e in env:
-            key, *value = e.split("=", maxsplit=1)
-            value = shlex.quote(value[0]) if len(value) > 0 else ""
-            if not all(c.isalnum() or c == "_" for c in key):
-                log_warning(
-                    f"'{e}' is an invalid environment variable so it is ignored"
-                )
-                continue
-            script += f"env[{repr(key)}] = {repr(value)}\n"
-
-        # Make the temporary files
-        for env_name, content in files.items():
-            script += "_, fname = tempfile.mkstemp()\n"
-            script += "with open(fname, 'w') as f:\n"
-            script += f"    f.write({repr(content)})\n"
-            script += f"env[{repr(env_name)}] = fname\n"
-
-        # Finally add the rank
-        script += f"env['MLX_RANK'] = '{rank}'\n"
-        script += "\n"
-
-        # Replace the process with the script
-        script += f"command = [{','.join(map(repr, command))}]\n"
-        script += "os.execve(command[0], command, env)\n"
-
-        return script
-
-
-def _launch_with_io(command_class, arguments, verbose):
-    stop = False
-    exit_codes = [(None, None)] * len(arguments)
-
-    def _thread_fn(rank, *args, **kwargs):
-        stdin_queue = kwargs.pop("stdin_queue")
-        stdout_queue = kwargs.pop("stdout_queue")
-        stderr_queue = kwargs.pop("stderr_queue")
-
-        command = command_class(rank, *args, **kwargs)
-        p = command.process
-        os.set_blocking(p.stdout.fileno(), False)
-        os.set_blocking(p.stderr.fileno(), False)
-        os.set_blocking(p.stdin.fileno(), False)
-
-        to_read = [p.stdout.fileno(), p.stderr.fileno()]
-        to_write = [p.stdin.fileno()]
-
-        stdin_buffer = b""
-        while p.poll() is None:
-            try:
-                stdin_buffer += stdin_queue.get_nowait()
-            except QueueEmpty:
-                pass
-            rlist, wlist, _ = select(to_read, to_write, [], 1.0)
-            for fd in rlist:
-                is_stdout = fd == p.stdout.fileno()
-                msg = os.read(fd, 8192).decode(errors="ignore")
-                msg = command.preprocess_output(msg, is_stdout)
-                if is_stdout:
-                    stdout_queue.put(msg.encode())
-                else:
-                    stderr_queue.put(msg.encode())
-            for fd in wlist:
-                if len(stdin_buffer) > 0:
-                    n = os.write(fd, stdin_buffer)
-                    stdin_buffer = stdin_buffer[n:]
-            if stop:
-                command.terminate()
-                break
-        exit_codes[rank] = command.exit_status
-
-        if exit_codes[rank][1]:
-            log_warning(f"Node with rank {rank} was killed")
-        elif exit_codes[rank][0] != 0:
-            log_warning(f"Node with rank {rank} exited with code {exit_codes[rank][0]}")
-        else:
-            log(verbose, f"Node with rank {rank} completed")
-
-    stdin_queues = []
-    stdout_queues = []
-    stderr_queues = []
-    threads = []
-    for i, (args, kwargs) in enumerate(arguments):
-        stdin_queues.append(Queue())
-        stdout_queues.append(Queue())
-        stderr_queues.append(Queue())
-        t = threading.Thread(
-            target=_thread_fn,
-            args=args,
-            kwargs=kwargs
-            | {
-                "stdin_queue": stdin_queues[-1],
-                "stdout_queue": stdout_queues[-1],
-                "stderr_queue": stderr_queues[-1],
-            },
-        )
-        t.start()
-        threads.append(t)
-
-    os.set_blocking(sys.stdin.fileno(), False)
-    os.set_blocking(sys.stdout.fileno(), True)
-    os.set_blocking(sys.stderr.fileno(), True)
-    while not stop or any(not q.empty() for q in chain(stdout_queues, stderr_queues)):
-        # Broadcast user input to the jobs
-        rlist, _, _ = select([sys.stdin.fileno()], [], [], 0.1)
-        for fd in rlist:
-            stdin_buffer = os.read(fd, 8192)
-            for q in stdin_queues:
-                q.put(stdin_buffer)
-
-        # Gather job output
-        for q in stdout_queues:
-            try:
-                while not q.empty():
-                    sys.stdout.buffer.write(q.get_nowait())
-            except QueueEmpty:
-                pass
-        for q in stderr_queues:
-            try:
-                while not q.empty():
-                    sys.stderr.buffer.write(q.get_nowait())
-            except QueueEmpty:
-                pass
-        sys.stdout.buffer.flush()
-        sys.stderr.buffer.flush()
-
-        # Check if all are running and terminate otherwise
-        if any(t.is_alive() for t in threads):
-            for i, t in enumerate(threads):
-                if not t.is_alive():
-                    if exit_codes[i][0] != 0:
-                        stop = True
-                        break
-        else:
-            break
-
-    # Wait for the jobs to finish
-    for t in threads:
-        t.join()
-
-    # Process any remaining outputs
-    for q in stdout_queues:
-        while not q.empty():
-            sys.stdout.buffer.write(q.get())
-    for q in stderr_queues:
-        while not q.empty():
-            sys.stderr.buffer.write(q.get())
-    sys.stdout.buffer.flush()
-    sys.stderr.buffer.flush()
-
-
-def launch_ring(parser, hosts, args, command):
-    if any(len(h.ips) == 0 for h in hosts):
-        parser.error(
-            "The ring backend requires IPs to be provided instead of hostnames"
-        )
-
-    port = args.starting_port
-    ring_hosts = []
-    for h in hosts:
-        node = []
-        for ip in h.ips:
-            for i in range(args.connections_per_ip):
-                node.append(f"{ip}:{port}")
-                port += 1
-        ring_hosts.append(node)
-    hostfile = json.dumps(ring_hosts) if len(ring_hosts) > 1 else ""
-
-    files = {"MLX_HOSTFILE": hostfile}
-    env = args.env
-    if args.verbose:
-        env.append("MLX_RING_VERBOSE=1")
-    cwd = args.cwd
-
-    log(args.verbose, "Running", shlex.join(command))
-
-    _launch_with_io(
-        RemoteProcess,
-        [
-            ((rank, h.ssh_hostname, cwd, files, env, command), {})
-            for rank, h in enumerate(hosts)
-        ],
-        args.verbose,
-    )
-
-
-def launch_nccl(parser, hosts, args, command):
-    if not hosts[0].ips:
-        raise ValueError("Rank 0 should have an IP reachable from all other ranks")
-
-    master_host = hosts[0].ips[0]
-    master_port = args.nccl_port
-    world_size = len(hosts)
-
-    env = args.env
-    cwd = args.cwd
-    if args.verbose:
-        env.append("NCCL_DEBUG=INFO")
-    env.append(f"NCCL_HOST_IP={master_host}")
-    env.append(f"NCCL_PORT={master_port}")
-    env.append(f"MLX_WORLD_SIZE={world_size}")
-
-    log(args.verbose, "Running", shlex.join(command))
-
-    _launch_with_io(
-        RemoteProcess,
-        [
-            (
-                (
-                    rank,
-                    h.ssh_hostname,
-                    cwd,
-                    {},
-                    env + [f"CUDA_VISIBLE_DEVICES={rank % args.repeat_hosts}"],
-                    command,
-                ),
-                {},
-            )
-            for rank, h in enumerate(hosts)
-        ],
-        args.verbose,
-    )
-
-
-def launch_jaccl(parser, hosts, args, command):
-    if not hosts[0].ips:
-        raise ValueError("Rank 0 should have an IP reachable from all other ranks")
-
-    have_rdmas = all(len(h.rdma) == len(hosts) for h in hosts)
-    have_nulls = all(h.rdma[i] is None for i, h in enumerate(hosts))
-    if not have_rdmas or not have_nulls:
-        raise ValueError("Malformed hostfile for jaccl backend")
-
-    coordinator = hosts[0].ips[0]
-    env = args.env
-    cwd = args.cwd
-    env.append(f"MLX_JACCL_COORDINATOR={coordinator}:{args.starting_port}")
-    files = {"MLX_IBV_DEVICES": json.dumps([h.rdma for h in hosts])}
-
-    log(args.verbose, "Running", shlex.join(command))
-
-    _launch_with_io(
-        RemoteProcess,
-        [
-            ((rank, h.ssh_hostname, cwd, files, env, command), {})
-            for rank, h in enumerate(hosts)
-        ],
-        args.verbose,
-    )
-
-
-def get_mpi_libname():
-    try:
-        ompi_info = run(["which", "ompi_info"], check=True, capture_output=True)
-        ompi_info = ompi_info.stdout.strip().decode()
-
-        if platform.system() == "Darwin":
-            otool_output = run(
-                ["otool", "-L", ompi_info], check=True, capture_output=True
-            )
-        else:
-            otool_output = run(["ldd", ompi_info], check=True, capture_output=True)
-        otool_output = otool_output.stdout.decode()
-
-        # StopIteration if not found
-        libmpi_line = next(
-            filter(lambda line: "libmpi" in line, otool_output.splitlines())
-        )
-        return libmpi_line.strip().split()[0].removeprefix("@rpath/")
-    except:
-        return None
-
-
-def launch_mpi(parser, hosts, args, command):
-    mpirun = run(["which", "mpirun"], check=True, capture_output=True)
-    mpirun = mpirun.stdout.strip().decode()
-
-    # Compatibility with homebrew and pip installs
-    mpi_libname = get_mpi_libname()
-    if mpi_libname is not None:
-        dyld = Path(mpirun).parent.parent / "lib"
-        args.env = [
-            f"DYLD_LIBRARY_PATH={str(dyld)}",
-            f"MLX_MPI_LIBNAME={mpi_libname}",
-        ] + args.env
-
-    log(args.verbose, f"Using '{mpirun}'")
-    with tempfile.NamedTemporaryFile(mode="w") as f:
-        hosts = Counter((h.ssh_hostname for h in hosts))
-        for h, n in hosts.items():
-            print(f"{h} slots={n}", file=f)
-        f.flush()
-
-        cmd = [
-            mpirun,
-            "--output",
-            ":raw",  # do not line buffer output
-            "--hostfile",
-            f.name,
-            *(["-cwd", args.cwd] if args.cwd else []),
-            *sum((["-x", e] for e in args.env), []),
-            *sum([shlex.split(arg) for arg in args.mpi_arg], []),
-            "--",
-            *command,
-        ]
-        log(args.verbose, "Running", " ".join(cmd))
-        try:
-            run(cmd)
-        except KeyboardInterrupt:
-            pass
-
-
-def main():
-    parser = argparse.ArgumentParser(description="Launch an MLX distributed program")
-    parser.add_argument(
-        "--print-python",
-        action="store_true",
-        help="Print the path to the current python executable and exit",
-    )
-    parser.add_argument(
-        "--verbose", action="store_true", help="Print debug messages in stdout"
-    )
-    parser.add_argument(
-        "--hosts", default="127.0.0.1", help="A comma separated list of hosts"
-    )
-    parser.add_argument(
-        "--repeat-hosts",
-        "-n",
-        type=positive_number,
-        default=1,
-        help="Repeat each host a given number of times",
-    )
-    parser.add_argument("--hostfile", help="The file containing the hosts")
-    parser.add_argument(
-        "--backend",
-        choices=["ring", "mpi", "nccl", "jaccl"],
-        default="nccl" if mx.cuda.is_available() else "ring",
-        help="Which distributed backend to launch",
-    )
-    parser.add_argument(
-        "--env",
-        action="append",
-        default=[],
-        help="Set environment variables for the jobs",
-    )
-    parser.add_argument(
-        "--mpi-arg",
-        action="append",
-        default=[],
-        help="Arguments to pass directly to mpirun",
-    )
-    parser.add_argument(
-        "--connections-per-ip",
-        default=1,
-        type=int,
-        help="How many connections per ip to use for the ring backend",
-    )
-    parser.add_argument(
-        "--starting-port",
-        "-p",
-        type=int,
-        default=32323,
-        help="For the ring backend listen on this port increasing by 1 per rank and IP",
-    )
-    parser.add_argument(
-        "--cwd", help="Set the working directory on each node to the provided one"
-    )
-    parser.add_argument(
-        "--nccl-port",
-        type=int,
-        default=12345,
-        help="The port to use for the NCCL communication (only for nccl backend)",
-    )
-
-    args, rest = parser.parse_known_args()
-
-    if args.print_python:
-        print(sys.executable)
-        return
-
-    if len(rest) == 0:
-        parser.error("No script is provided")
-    if rest[0] == "--":
-        rest.pop(0)
-
-    # Try to extract a list of hosts and corresponding ips
-    if args.hostfile is not None:
-        hosts = parse_hostfile(parser, args.hostfile)
-    else:
-        hosts = parse_hostlist(parser, args.hosts, args.repeat_hosts)
-
-    # Check if the script is a file and convert it to a full path
-    if (script := Path(rest[0])).exists() and script.is_file():
-        rest[0:1] = [sys.executable, str(script.resolve())]
-    elif (command := shutil.which(rest[0])) is not None:
-        rest[0] = command
-    else:
-        raise ValueError(f"Invalid script or command {rest[0]}")
-
-    # Launch
-    if args.backend == "ring":
-        launch_ring(parser, hosts, args, rest)
-    if args.backend == "mpi":
-        launch_mpi(parser, hosts, args, rest)
-    if args.backend == "nccl":
-        launch_nccl(parser, hosts, args, rest)
-    if args.backend == "jaccl":
-        launch_jaccl(parser, hosts, args, rest)

python/mlx/distributed_run.py

@@ -832,7 +832,7 @@ def main():
     parser.add_argument("--hostfile", help="The file containing the hosts")
     parser.add_argument(
         "--backend",
-        choices=["ring", "mpi", "nccl", "jaccl"],
+        choices=["ring", "mpi", "nccl"],
         default="nccl" if mx.cuda.is_available() else "ring",
         help="Which distributed backend to launch",
     )
@@ -903,8 +903,6 @@ def main():
         launch_mpi(parser, hosts, args, rest)
     if args.backend == "nccl":
         launch_nccl(parser, hosts, args, rest)
-    if args.backend == "jaccl":
-        launch_jaccl(parser, hosts, args, rest)
 
 
 if __name__ == "__main__":

python/scripts/repair_cuda.sh

@@ -1,7 +1,7 @@
 #!/bin/bash
 
 auditwheel repair dist/* \
-  --plat manylinux_2_35_x86_64 \
+  --plat manylinux_2_35_${1} \
   --exclude libcublas* \
   --exclude libnvrtc* \
   --exclude libcuda* \

python/src/distributed.cpp

@@ -52,25 +52,9 @@ void init_distributed(nb::module_& parent_module) {
 
   m.def(
       "is_available",
-      [](const std::string& backend) {
+      &mx::distributed::is_available,
-        return mx::distributed::is_available(backend);
-      },
-      "backend"_a = "any",
-      nb::sig("def is_available(backend: str = 'any') -> bool"),
       R"pbdoc(
       Check if a communication backend is available.
-
-      Note, this function returns whether MLX has the capability of
-      instantiating that distributed backend not whether it is possible to
-      create a communication group. For that purpose one should use
-      ``init(strict=True)``.
-
-      Args:
-        backend (str, optional): The name of the backend to check for availability.
-          It takes the same values as ``init()``. Default: ``any``.
-
-      Returns:
-        bool: Whether the distributed backend is available.
       )pbdoc");
 
   m.def(
@@ -95,10 +79,10 @@ void init_distributed(nb::module_& parent_module) {
             in case ``mx.distributed.is_available()`` returns False otherwise
             it throws a runtime error. Default: ``False``
           backend (str, optional): Which distributed backend to initialize.
-            Possible values ``mpi``, ``ring``, ``nccl``, ``jaccl``, ``any``. If
+            Possible values ``mpi``, ``ring``, ``nccl``, ``any``. If set to ``any`` all
-            set to ``any`` all available backends are tried and the first one
+            available backends are tried and the first one that succeeds
-            that succeeds becomes the global group which will be returned in
+            becomes the global group which will be returned in subsequent
-            subsequent calls. Default: ``any``
+            calls. Default: ``any``
 
         Returns:
           Group: The group representing all the launched processes.

python/tests/test_reduce.py

@@ -210,6 +210,14 @@ class TestReduce(mlx_tests.MLXTestCase):
                     ref = getattr(np, op)(np_arr, axis=axis)
                     self.assertTrue(np.array_equal(out, ref, equal_nan=True))
 
+    def test_long_column(self):
+        a = (np.random.randn(8192, 64) * 32).astype(np.int32)
+        b = mx.array(a)
+
+        c1 = a.sum(0)
+        c2 = b.sum(0)
+        self.assertTrue(np.all(c1 == c2))
+
 
 if __name__ == "__main__":
     mlx_tests.MLXTestRunner(failfast=True)

setup.py

@@ -7,13 +7,21 @@ import re
 import subprocess
 from functools import partial
 from pathlib import Path
-from subprocess import run
 
 from setuptools import Command, Extension, find_namespace_packages, setup
 from setuptools.command.bdist_wheel import bdist_wheel
 from setuptools.command.build_ext import build_ext
 
 
+def cuda_toolkit_major_version():
+    out = subprocess.check_output(["nvcc", "--version"], stderr=subprocess.STDOUT)
+    text = out.decode()
+    m = re.search(r"release (\d+)", text)
+    if m:
+        return int(m.group(1))
+    return None
+
+
 def get_version():
     with open("mlx/version.h", "r") as fid:
         for l in fid:
@@ -31,7 +39,7 @@ def get_version():
         version = f"{version}.dev{today.year}{today.month:02d}{today.day:02d}"
     if not pypi_release and not dev_release:
         git_hash = (
-            run(
+            subprocess.run(
                 "git rev-parse --short HEAD".split(),
                 capture_output=True,
                 check=True,
@@ -257,8 +265,8 @@ if __name__ == "__main__":
     }
     entry_points = {
         "console_scripts": [
-            "mlx.launch = mlx._distributed_utils.launch:main",
+            "mlx.launch = mlx.distributed_run:main",
-            # "mlx.distributed_config = mlx.distributed_run:distributed_config",
+            "mlx.distributed_config = mlx.distributed_run:distributed_config",
         ]
     }
     install_requires = []
@@ -284,7 +292,11 @@ if __name__ == "__main__":
             install_requires.append(
                 f'mlx-metal=={version}; platform_system == "Darwin"'
             )
-            extras["cuda"] = [f'mlx-cuda=={version}; platform_system == "Linux"']
+            extras["cuda"] = [f'mlx-cuda-12=={version}; platform_system == "Linux"']
+            for toolkit in [12, 13]:
+                extras[f"cuda{toolkit}"] = [
+                    f'mlx-cuda-{toolkit}=={version}; platform_system == "Linux"'
+                ]
             extras["cpu"] = [f'mlx-cpu=={version}; platform_system == "Linux"']
 
         _setup(
@@ -299,13 +311,25 @@ if __name__ == "__main__":
         if build_macos:
             name = "mlx-metal"
         elif build_cuda:
-            name = "mlx-cuda"
+            toolkit = cuda_toolkit_major_version()
+            name = f"mlx-cuda-{toolkit}"
+            if toolkit == 12:
                 install_requires += [
                     "nvidia-cublas-cu12==12.9.*",
                     "nvidia-cuda-nvrtc-cu12==12.9.*",
-                "nvidia-cudnn-cu12==9.*",
-                "nvidia-nccl-cu12",
                 ]
+            elif toolkit == 13:
+                install_requires += [
+                    "nvidia-cublas-cu13",
+                    "nvidia-cuda-nvrtc-cu13",
+                ]
+            else:
+                raise ValueError(f"Unknown toolkit {toolkit}")
+            install_requires += [
+                f"nvidia-cudnn-cu{toolkit}==9.*",
+                f"nvidia-nccl-cu{toolkit}",
+            ]
+
         else:
             name = "mlx-cpu"
         _setup(

tests/array_tests.cpp

@@ -1,5 +1,4 @@
 // Copyright © 2023 Apple Inc.
-
 #include <climits>
 
 #include "doctest/doctest.h"
@@ -608,3 +607,24 @@ TEST_CASE("test make empty array") {
   CHECK_EQ(a.size(), 0);
   CHECK_EQ(a.dtype(), bool_);
 }
+
+TEST_CASE("test make array from user buffer") {
+  int size = 4096;
+  std::vector<int> buffer(size, 0);
+
+  int count = 0;
+  auto deleter = [&count](void*) { count++; };
+
+  {
+    auto a = array(buffer.data(), Shape{size}, int32, deleter);
+    if (metal::is_available()) {
+      CHECK_EQ(buffer.data(), a.data<int>());
+    }
+    auto b = a + array(1);
+    eval(b);
+    auto expected = ones({4096});
+    CHECK(array_equal(b, expected).item<bool>());
+  }
+  // deleter should always get called
+  CHECK_EQ(count, 1);
+}