[CUDA] synch properly waits for all tasks to finish and clear (#2303)

* cuda synch properly waits for all tasks to finish and clear

* fix copy

mlx/backend/cuda/allocator.cpp

@@ -106,7 +106,6 @@ void CudaAllocator::cuda_free(void* buf) {
       return;
     }
   }
-
   cudaFree(buf);
 }
 

mlx/backend/cuda/copy/copy_general.cu

@@ -63,25 +63,30 @@ void copy_general(
       MLX_SWITCH_BOOL(large, LARGE, {
         using IdxT = std::conditional_t<LARGE, int64_t, int32_t>;
         int ndim = shape.size();
+        size_t data_size = 1;
+        for (auto& s : shape)
+          data_size *= s;
         if (ndim <= 3) {
           MLX_SWITCH_1_2_3(ndim, NDIM, {
             auto kernel = cu::copy_gg_nd<InType, OutType, IdxT, NDIM>;
-            auto [num_blocks, block_dims] = get_launch_args(kernel, out, large);
+            auto [num_blocks, block_dims] =
+                get_launch_args(kernel, data_size, shape, out.strides(), large);
             kernel<<<num_blocks, block_dims, 0, stream>>>(
                 in_ptr,
                 out_ptr,
-                out.size(),
+                data_size,
                 const_param<NDIM>(shape),
                 const_param<NDIM>(strides_in),
                 const_param<NDIM>(strides_out));
           });
         } else { // ndim >= 4
           auto kernel = cu::copy_gg<InType, OutType, IdxT>;
-          auto [num_blocks, block_dims] = get_launch_args(kernel, out, large);
+          auto [num_blocks, block_dims] =
+              get_launch_args(kernel, data_size, shape, out.strides(), large);
           kernel<<<num_blocks, block_dims, 0, stream>>>(
               in_ptr,
               out_ptr,
-              out.size(),
+              data_size,
               const_param(shape),
               const_param(strides_in),
               const_param(strides_out),

mlx/backend/cuda/device.cpp

@@ -6,6 +6,7 @@
 
 #include <fmt/format.h>
 #include <nvtx3/nvtx3.hpp>
+#include <future>
 
 namespace mlx::core {
 
@@ -107,6 +108,16 @@ void CommandEncoder::commit() {
   worker_.commit(stream_.last_cuda_stream());
 }
 
+void CommandEncoder::synchronize() {
+  stream().synchronize();
+  auto p = std::make_shared<std::promise<void>>();
+  std::future<void> f = p->get_future();
+  add_completed_handler([p = std::move(p)]() { p->set_value(); });
+  worker_.end_batch();
+  worker_.commit();
+  f.wait();
+}
+
 Device& device(mlx::core::Device device) {
   static std::unordered_map<int, Device> devices;
   auto it = devices.find(device.index);

mlx/backend/cuda/device.h

@@ -123,6 +123,9 @@ class CommandEncoder {
     return has_gpu_work_;
   }
 
+  // Wait until kernels and completion handlers are finished
+  void synchronize();
+
  private:
   Device& device_;
   DeviceStream& stream_;

mlx/backend/cuda/eval.cpp

@@ -62,7 +62,7 @@ void finalize(Stream s) {
 
 void synchronize(Stream s) {
   nvtx3::scoped_range r("gpu::synchronize");
-  cu::get_stream(s).synchronize();
+  cu::get_command_encoder(s).synchronize();
 }
 
 } // namespace mlx::core::gpu

mlx/backend/cuda/worker.cpp

@@ -80,7 +80,9 @@ void Worker::thread_fn() {
       }
       worker_tasks_.erase(worker_tasks_.begin(), end);
     }
-    for (auto& task : tasks) {
+    // Make sure tasks are cleared before the next wait
+    for (int i = 0; i < tasks.size(); ++i) {
+      auto task = std::move(tasks[i]);
       task();
     }
     worker_event_.wait(batch + 1);

python/tests/cuda_skip.py

@@ -6,7 +6,6 @@ cuda_skip = {
     "TestEinsum.test_ellipses",
     "TestEinsum.test_opt_einsum_test_cases",
     "TestLoad.test_load_f8_e4m3",
-    "TestMemory.test_memory_info",
     "TestLayers.test_group_norm",
     "TestLayers.test_pooling",
     "TestLayers.test_quantized_embedding",