MPI ops in GPU stream for faster comms (#1356)

benchmarks/python/distributed_bench.py

@@ -0,0 +1,66 @@
+# Copyright © 2024 Apple Inc.
+
+"""
+Run with:
+    mpirun -n 2 python /path/to/distributed_bench.py
+"""
+
+import time
+
+import mlx.core as mx
+
+
+def time_fn(fn, *args, **kwargs):
+    msg = kwargs.pop("msg", None)
+    world = mx.distributed.init()
+    if world.rank() == 0:
+        if msg:
+            print(f"Timing {msg} ...", end=" ")
+        else:
+            print(f"Timing {fn.__name__} ...", end=" ")
+
+    # warmup
+    for _ in range(5):
+        mx.eval(fn(*args, **kwargs))
+
+    num_iters = 100
+    tic = time.perf_counter()
+    for _ in range(num_iters):
+        x = mx.eval(fn(*args, **kwargs))
+    toc = time.perf_counter()
+
+    msec = 1e3 * (toc - tic) / num_iters
+    if world.rank() == 0:
+        print(f"{msec:.5f} msec")
+
+
+def time_all_sum():
+    shape = (4096,)
+    x = mx.random.uniform(shape=shape)
+    mx.eval(x)
+
+    def sine(x):
+        for _ in range(20):
+            x = mx.sin(x)
+        return x
+
+    time_fn(sine, x)
+
+    def all_sum_plain(x):
+        for _ in range(20):
+            x = mx.distributed.all_sum(x)
+        return x
+
+    time_fn(all_sum_plain, x)
+
+    def all_sum_with_sine(x):
+        for _ in range(20):
+            x = mx.sin(x)
+            x = mx.distributed.all_sum(x)
+        return x
+
+    time_fn(all_sum_with_sine, x)
+
+
+if __name__ == "__main__":
+    time_all_sum()

mlx/backend/metal/CMakeLists.txt

@@ -132,6 +132,7 @@ target_sources(
   ${CMAKE_CURRENT_SOURCE_DIR}/conv.cpp
   ${CMAKE_CURRENT_SOURCE_DIR}/copy.cpp
   ${CMAKE_CURRENT_SOURCE_DIR}/custom_kernel.cpp
+  ${CMAKE_CURRENT_SOURCE_DIR}/distributed.cpp
   ${CMAKE_CURRENT_SOURCE_DIR}/device.cpp
   ${CMAKE_CURRENT_SOURCE_DIR}/event.cpp
   ${CMAKE_CURRENT_SOURCE_DIR}/fft.cpp

mlx/backend/metal/distributed.cpp

@@ -0,0 +1,84 @@
+// Copyright © 2024 Apple Inc.
+
+#include <cassert>
+
+#include "mlx/allocator.h"
+#include "mlx/backend/metal/device.h"
+#include "mlx/distributed/ops.h"
+#include "mlx/distributed/primitives.h"
+#include "mlx/scheduler.h"
+
+namespace mlx::core::distributed {
+
+void signal_and_wait(const array& in, const array& out, const Stream s) {
+  auto& d = metal::device(s.device);
+  d.end_encoding(s.index);
+  auto command_buffer = d.get_command_buffer(s.index);
+  if (in.event().valid()) {
+    command_buffer->encodeSignalEvent(
+        static_cast<MTL::Event*>(in.event().raw_event().get()),
+        in.event().value());
+  }
+  command_buffer->encodeWait(
+      static_cast<MTL::Event*>(out.event().raw_event().get()),
+      out.event().value());
+}
+
+void AllReduce::eval_gpu(
+    const std::vector<array>& inputs,
+    std::vector<array>& outputs) {
+  assert(inputs.size() == 1);
+  assert(outputs.size() == 1);
+
+  auto& in = inputs[0];
+  auto& out = outputs[0];
+  if (in.is_donatable()) {
+    out.move_shared_buffer(in);
+  } else {
+    out.set_data(allocator::malloc_or_wait(out.nbytes()));
+  }
+
+  auto task = [in = in,
+               out = out,
+               reduce_type = reduce_type_,
+               group = group()]() mutable {
+    if (in.event().valid()) {
+      in.event().wait();
+    }
+    switch (reduce_type) {
+      case Sum:
+        distributed::detail::all_sum(
+            group, in.data_shared_ptr() == nullptr ? out : in, out);
+        break;
+      default:
+        throw std::runtime_error("Only all reduce sum is supported for now");
+    }
+    out.event().signal();
+  };
+  scheduler::enqueue(detail::communication_stream(), std::move(task));
+
+  signal_and_wait(in, out, stream());
+}
+
+void AllGather::eval_gpu(
+    const std::vector<array>& inputs,
+    std::vector<array>& outputs) {
+  assert(inputs.size() == 1);
+  assert(outputs.size() == 1);
+  auto& in = inputs[0];
+  auto& out = outputs[0];
+
+  out.set_data(allocator::malloc_or_wait(out.nbytes()));
+
+  auto task = [in = in, out = out, group = group()]() mutable {
+    if (in.event().valid()) {
+      in.event().wait();
+    }
+    distributed::detail::all_gather(group, in, out);
+    out.event().signal();
+  };
+  scheduler::enqueue(detail::communication_stream(), std::move(task));
+  signal_and_wait(in, out, stream());
+}
+
+} // namespace mlx::core::distributed

mlx/backend/metal/metal.cpp

@@ -47,8 +47,6 @@ std::function<void()> make_task(array arr, bool signal) {
     for (auto& input : arr.inputs()) {
       if (input.event().valid() &&
           input.event().stream() != arr.primitive().stream()) {
-        // TODO, consider committing the buffer and encoding a wait in the new
-        // buffer rather than on the task thread
         input.event().wait();
       }
     }

mlx/backend/no_metal/primitives.cpp

@@ -1,6 +1,7 @@
 // Copyright © 2023-2024 Apple Inc.
 
 #include "mlx/primitives.h"
+#include "mlx/distributed/primitives.h"
 #include "mlx/fast_primitives.h"
 
 #define NO_GPU_MULTI(func)                                             \
@@ -122,4 +123,9 @@ NO_GPU_MULTI(AffineQuantize)
 NO_GPU_MULTI(CustomKernel)
 } // namespace fast
 
+namespace distributed {
+NO_GPU_MULTI(AllReduce)
+NO_GPU_MULTI(AllGather)
+} // namespace distributed
+
 } // namespace mlx::core

mlx/distributed/distributed_impl.h

@@ -0,0 +1,18 @@
+// Copyright © 2024 Apple Inc.
+
+#pragma once
+
+#include "mlx/distributed/distributed.h"
+
+namespace mlx::core::distributed::detail {
+
+/* Return the communication stream. */
+Stream communication_stream();
+
+/* Perform an all reduce sum operation */
+void all_sum(Group group, const array& input, array& output);
+
+/* Perform an all reduce sum operation */
+void all_gather(Group group, const array& input, array& output);
+
+} // namespace mlx::core::distributed::detail

mlx/distributed/mpi/mpi.cpp

@@ -5,6 +5,7 @@
 
 #include "mlx/backend/common/copy.h"
 #include "mlx/distributed/distributed.h"
+#include "mlx/distributed/distributed_impl.h"
 #include "mlx/scheduler.h"
 
 #define LOAD_SYMBOL(symbol, variable)                              \

mlx/distributed/no_distributed.cpp

@@ -1,6 +1,7 @@
 // Copyright © 2024 Apple Inc.
 
 #include "mlx/distributed/distributed.h"
+#include "mlx/distributed/distributed_impl.h"
 
 namespace mlx::core::distributed {
 

mlx/distributed/ops.cpp

@@ -17,7 +17,10 @@ Group to_group(std::optional<Group> group) {
 
 } // namespace
 
-array all_sum(const array& x, std::optional<Group> group_) {
+array all_sum(
+    const array& x,
+    std::optional<Group> group_ /* = std::nullopt */,
+    StreamOrDevice s /* = {} */) {
   auto group = to_group(group_);
 
   if (group.size() == 1) {
@@ -27,11 +30,14 @@ array all_sum(const array& x, std::optional<Group> group_) {
   return array(
       x.shape(),
       x.dtype(),
-      std::make_shared<AllReduce>(group, AllReduce::Sum),
+      std::make_shared<AllReduce>(to_stream(s), group, AllReduce::Sum),
       {x});
 }
 
-array all_gather(const array& x, std::optional<Group> group_) {
+array all_gather(
+    const array& x,
+    std::optional<Group> group_ /* = std::nullopt */,
+    StreamOrDevice s /* = {} */) {
   auto group = to_group(group_);
 
   if (group.size() == 1) {
@@ -47,7 +53,7 @@ array all_gather(const array& x, std::optional<Group> group_) {
   return array(
       std::move(result_shape),
       x.dtype(),
-      std::make_shared<AllGather>(group),
+      std::make_shared<AllGather>(to_stream(s), group),
       {x});
 }
 

mlx/distributed/ops.h

@@ -5,10 +5,17 @@
 #include <optional>
 
 #include "mlx/distributed/distributed.h"
+#include "mlx/utils.h"
 
 namespace mlx::core::distributed {
 
-array all_sum(const array& x, std::optional<Group> group = std::nullopt);
-array all_gather(const array& x, std::optional<Group> group = std::nullopt);
+array all_sum(
+    const array& x,
+    std::optional<Group> group = std::nullopt,
+    StreamOrDevice s = {});
+array all_gather(
+    const array& x,
+    std::optional<Group> group = std::nullopt,
+    StreamOrDevice S = {});
 
 } // namespace mlx::core::distributed

mlx/distributed/primitives.cpp

@@ -3,7 +3,6 @@
 #include <cassert>
 
 #include "mlx/allocator.h"
-#include "mlx/backend/common/copy.h"
 #include "mlx/distributed/ops.h"
 #include "mlx/distributed/primitives.h"
 #include "mlx/ops.h"

mlx/distributed/primitives.h

@@ -3,20 +3,15 @@
 #pragma once
 
 #include "mlx/distributed/distributed.h"
+#include "mlx/distributed/distributed_impl.h"
 #include "mlx/primitives.h"
 
 namespace mlx::core::distributed {
 
 class DistPrimitive : public Primitive {
  public:
-  DistPrimitive(Group group)
-      : Primitive(detail::communication_stream()), group_(group) {}
-
-  void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
-      override {
-    throw std::runtime_error(
-        "Communication primitives cannot be run on the GPU");
-  }
+  DistPrimitive(Stream stream, Group group)
+      : Primitive(stream), group_(group) {}
 
   const Group& group() const {
     return group_;
@@ -30,11 +25,13 @@ class AllReduce : public DistPrimitive {
  public:
   enum ReduceType { And, Or, Sum, Prod, Min, Max };
 
-  AllReduce(Group group, ReduceType reduce_type)
-      : DistPrimitive(group), reduce_type_(reduce_type) {}
+  AllReduce(Stream stream, Group group, ReduceType reduce_type)
+      : DistPrimitive(stream, group), reduce_type_(reduce_type) {}
 
   void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
       override;
+  void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
+      override;
   std::pair<std::vector<array>, std::vector<int>> vmap(
       const std::vector<array>& inputs,
       const std::vector<int>& axes) override;
@@ -77,10 +74,13 @@ class AllReduce : public DistPrimitive {
 
 class AllGather : public DistPrimitive {
  public:
-  AllGather(Group group) : DistPrimitive(group) {}
+  AllGather(Stream stream, Group group) : DistPrimitive(stream, group) {}
 
   void eval_cpu(const std::vector<array>& inputs, std::vector<array>& outputs)
       override;
+  void eval_gpu(const std::vector<array>& inputs, std::vector<array>& outputs)
+      override;
+
   std::pair<std::vector<array>, std::vector<int>> vmap(
       const std::vector<array>& inputs,
       const std::vector<int>& axes) override;

mlx/utils.h

@@ -4,10 +4,10 @@
 
 #include <variant>
 
-#include "array.h"
-#include "device.h"
-#include "dtype.h"
-#include "stream.h"
+#include "mlx/array.h"
+#include "mlx/device.h"
+#include "mlx/dtype.h"
+#include "mlx/stream.h"
 
 namespace mlx::core {
 

python/src/distributed.cpp

@@ -3,6 +3,7 @@
 #include <nanobind/nanobind.h>
 #include <nanobind/stl/optional.h>
 #include <nanobind/stl/shared_ptr.h>
+#include <nanobind/stl/variant.h>
 
 #include "mlx/distributed/distributed.h"
 #include "mlx/distributed/ops.h"
@@ -74,8 +75,9 @@ void init_distributed(nb::module_& parent_module) {
       "x"_a,
       nb::kw_only(),
       "group"_a = nb::none(),
+      "stream"_a = nb::none(),
       nb::sig(
-          "def all_sum(x: array, *, group: Optional[Group] = None) -> array"),
+          "def all_sum(x: array, *, group: Optional[Group] = None, stream: Union[None, Stream, Device] = None) -> array"),
       R"pbdoc(
         All reduce sum.
 
@@ -86,6 +88,8 @@ void init_distributed(nb::module_& parent_module) {
           group (Group): The group of processes that will participate in the
             reduction. If set to ``None`` the global group is used. Default:
             ``None``.
+          stream (Stream, optional): Stream or device. Defaults to ``None``
+            in which case the default stream of the default device is used.
 
         Returns:
           array: The sum of all ``x`` arrays.
@@ -97,8 +101,9 @@ void init_distributed(nb::module_& parent_module) {
       "x"_a,
       nb::kw_only(),
       "group"_a = nb::none(),
+      "stream"_a = nb::none(),
       nb::sig(
-          "def all_gather(x: array, *, group: Optional[Group] = None) -> array"),
+          "def all_gather(x: array, *, group: Optional[Group] = None, stream: Union[None, Stream, Device] = None) -> array"),
       R"pbdoc(
         Gather arrays from all processes.
 
@@ -110,6 +115,8 @@ void init_distributed(nb::module_& parent_module) {
           group (Group): The group of processes that will participate in the
             gather. If set to ``None`` the global group is used. Default:
             ``None``.
+          stream (Stream, optional): Stream or device. Defaults to ``None``
+            in which case the default stream of the default device is used.
 
         Returns:
           array: The concatenation of all ``x`` arrays.