mlx/mlx/backend/cuda/distributed.cu
Awni Hannun 2afdf380b1 comment
2025-08-22 09:42:46 -07:00

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// Copyright © 2025 Apple Inc.
#include "mlx/backend/cuda/device.h"
#include "mlx/backend/cuda/kernel_utils.cuh"
#include "mlx/backend/gpu/copy.h"
#include "mlx/distributed/primitives.h"
#include "mlx/primitives.h"
#include <cassert>
namespace mlx::core::distributed {
void AllReduce::eval_gpu(
const std::vector<array>& inputs,
std::vector<array>& outputs) {
assert(inputs.size() == 1);
assert(outputs.size() == 1);
auto set_input_output =
[s = stream()](const array& in, array& out) -> std::pair<array, array> {
if (!in.flags().row_contiguous) {
copy_gpu(in, out, CopyType::General, s);
return {out, out};
} else if (in.is_donatable()) {
out.copy_shared_buffer(in);
return {in, out};
} else {
return {in, out};
}
};
auto [input, output] = set_input_output(inputs[0], outputs[0]);
auto& encoder = cu::get_command_encoder(stream());
encoder.set_input_array(input);
encoder.set_output_array(output);
auto capture = encoder.capture_context();
auto& s = stream();
switch (reduce_type_) {
case Sum:
distributed::detail::all_sum(group(), input, output, s);
break;
case Max:
distributed::detail::all_max(group(), input, output, s);
break;
case Min:
distributed::detail::all_min(group(), input, output, s);
break;
default:
throw std::runtime_error(
"Only all reduce sum, max, and min are supported.");
}
}
} // namespace mlx::core::distributed