[AMD] Support fast_topk kernels in sgl-kernel (#15172)
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1
.github/workflows/pr-test-amd.yml
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1
.github/workflows/pr-test-amd.yml
vendored
@@ -102,6 +102,7 @@ jobs:
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docker exec -w /sglang-checkout/sgl-kernel/tests/speculative ci_sglang python3 -m pytest test_eagle_utils.py
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docker exec -w /sglang-checkout/sgl-kernel/tests ci_sglang python3 -m pytest test_apply_token_bitmask_inplace.py
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docker exec -w /sglang-checkout/sgl-kernel/tests ci_sglang python3 -m pytest test_activation.py
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docker exec -w /sglang-checkout/sgl-kernel/tests ci_sglang python3 -m pytest test_topk.py
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docker exec -w /sglang-checkout/sgl-kernel/tests ci_sglang python3 -m pytest test_kvcacheio.py
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# =============================================== primary ====================================================
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@@ -20,7 +20,7 @@ limitations under the License.
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TORCH_LIBRARY_EXPAND(sgl_kernel, m) {
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/*
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* From csrc/activation
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* From csrc/elementwise
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*/
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m.def("silu_and_mul(Tensor! out, Tensor input) -> ()");
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m.impl("silu_and_mul", torch::kCUDA, &silu_and_mul);
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@@ -34,6 +34,19 @@ TORCH_LIBRARY_EXPAND(sgl_kernel, m) {
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m.def("gelu_quick(Tensor! out, Tensor input) -> ()");
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m.impl("gelu_quick", torch::kCUDA, &gelu_quick);
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m.def("fast_topk(Tensor score, Tensor indices, Tensor lengths, Tensor? row_starts) -> ()");
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m.impl("fast_topk", torch::kCUDA, &fast_topk_interface);
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m.def(
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"fast_topk_transform_fused(Tensor score, Tensor lengths, Tensor dst_page_table, Tensor src_page_table, Tensor "
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"cu_seqlens_q, Tensor? row_starts) -> ()");
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m.impl("fast_topk_transform_fused", torch::kCUDA, &fast_topk_transform_interface);
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m.def(
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"fast_topk_transform_ragged_fused(Tensor score, Tensor lengths, Tensor topk_indices_ragged, Tensor "
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"topk_indices_offset, Tensor ? row_starts) -> ()");
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m.impl("fast_topk_transform_ragged_fused", torch::kCUDA, &fast_topk_transform_ragged_interface);
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/*
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* From csrc/allreduce
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*/
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@@ -22,7 +22,18 @@ namespace {
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constexpr int TopK = 2048;
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constexpr int kThreadsPerBlock = 1024;
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constexpr size_t kSmem = 32 * 1024 * sizeof(uint32_t); // 128KB
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#ifdef USE_ROCM
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// On ROCm, the per-workgroup LDS budget depends on the target arch, so we inject a
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// per-arch value from `setup_rocm.py` via `-DSGL_TOPK_DYNAMIC_SMEM_BYTES=...`.
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#ifdef SGL_TOPK_DYNAMIC_SMEM_BYTES
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constexpr size_t kSmem = static_cast<size_t>(SGL_TOPK_DYNAMIC_SMEM_BYTES);
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#else
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constexpr size_t kSmem = 48 * 1024; // bytes
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#endif
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#else
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constexpr size_t kSmem = 32 * 1024 * sizeof(uint32_t); // 128KB (bytes)
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#endif
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struct FastTopKParams {
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const float* __restrict__ input; // [B, input_stride]
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@@ -401,8 +412,18 @@ auto get_params(
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template <auto* f, size_t max_dynamic_smem>
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void setup_kernel_smem_once() {
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[[maybe_unused]]
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static const auto result =
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[] { return ::cudaFuncSetAttribute(f, ::cudaFuncAttributeMaxDynamicSharedMemorySize, max_dynamic_smem); }();
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static const auto result = [] {
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#ifdef USE_ROCM
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// hipify will turn cudaFuncSetAttribute -> hipFuncSetAttribute. On ROCm,
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// hipFuncSetAttribute expects `const void*` and hipcc does not accept passing
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// a function pointer directly, so cast explicitly.
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return ::cudaFuncSetAttribute(
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reinterpret_cast<const void*>(f), ::cudaFuncAttributeMaxDynamicSharedMemorySize, max_dynamic_smem);
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#else
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// CUDA: keep original behavior (no cast needed).
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return ::cudaFuncSetAttribute(f, ::cudaFuncAttributeMaxDynamicSharedMemorySize, max_dynamic_smem);
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#endif
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}();
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TORCH_CHECK(result == cudaSuccess, "set_up_kernel_once failed:", ::cudaGetErrorString(result));
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}
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@@ -46,6 +46,7 @@ sources = [
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"csrc/allreduce/quick_all_reduce.cu",
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"csrc/common_extension_rocm.cc",
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"csrc/elementwise/activation.cu",
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"csrc/elementwise/topk.cu",
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"csrc/grammar/apply_token_bitmask_inplace_cuda.cu",
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"csrc/moe/moe_align_kernel.cu",
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"csrc/moe/moe_topk_softmax_kernels.cu",
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@@ -80,6 +81,12 @@ fp8_macro = (
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"-DHIP_FP8_TYPE_FNUZ" if amdgpu_target == "gfx942" else "-DHIP_FP8_TYPE_E4M3"
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)
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# Dynamic shared-memory budget for the TopK kernels.
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# - gfx942 (MI300/MI325): LDS is typically 64KB per workgroup -> keep dynamic smem <= ~48KB
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# (leaves room for static shared allocations in the kernel).
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# - gfx95x (MI350): LDS is larger (e.g. 160KB per CU) -> allow the original 128KB dynamic smem.
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topk_dynamic_smem_bytes = 48 * 1024 if amdgpu_target == "gfx942" else 32 * 1024 * 4
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hipcc_flags = [
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"-DNDEBUG",
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f"-DOPERATOR_NAMESPACE={operator_namespace}",
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@@ -91,6 +98,7 @@ hipcc_flags = [
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"-DENABLE_BF16",
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"-DENABLE_FP8",
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fp8_macro,
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f"-DSGL_TOPK_DYNAMIC_SMEM_BYTES={topk_dynamic_smem_bytes}",
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]
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ext_modules = [
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