Files
obsidian/projects/auto-tuner/Ongoing.md

107 lines
13 KiB
Markdown

## vLLM DBO 代码结构
```python
class UBatchWrapper:
def __init__(
self,
runnable: Callable,
vllm_config: VllmConfig,
runtime_mode: CUDAGraphMode,
device: torch.cuda.device,
):
self.runnable = runnable
self.vllm_config = vllm_config
self.compilation_config = vllm_config.compilation_config
self.comm_stream = torch.cuda.Stream(device=device)
# Two ubatch threads plus the main thread
self.ready_barrier = threading.Barrier(3)
self.cudagraphs: dict[int, CUDAGraphMetaData] = {}
self.cudagraph_wrapper = None
self.graph_pool = None
if runtime_mode is not CUDAGraphMode.NONE:
self.cudagraph_wrapper = CUDAGraphWrapper(
runnable, vllm_config, runtime_mode=runtime_mode
)
self.graph_pool = current_platform.get_global_graph_pool()
self.sm_control = self._create_sm_control_context(vllm_config)
self.device = device
```
https://github.com/vllm-project/vllm-ascend/issues/2599
in vllm, we can search PR for `[Core/DBO]`
## notes
> Could you provide some performance improvement data? I tested DeepSeek V2 Lite locally and observed a negative performance gain, with the per-step latency increasing from 38ms to 49ms. The process of launching vLLM and the test results are shown below.
> According to the Nsys profile data, after enabling DBO, the execution time of both kernel batched_triton_kerneland vllm::act_and_mul_kernelhas increased significantly.
Yes this is expected; DBO will increase the GEMM time when running a memory bound workload since the full model weights will have to be loaded twice (once for each microbatch). So DBO is only really beneficial when the communication time is >1x GEMM time; so it's really only intended to be used in multi-node EP setup where the communications costs are much higher. Its not expected to provide speed-up in a single node environment.
# kernels
```
ampere_bf16_s16816gemm_bf16_128x128_ldg8_f2f_stages_64x3_tn
ampere_bf16_s16816gemm_bf16_128x64_ldg8_f2f_stages_64x4_tn
ampere_bf16_s16816gemm_bf16_64x64_sliced1x2_ldg8_f2f_stages_64x5_tn
ampere_bf16_s16816gemm_bf16_64x64_sliced1x2_ldg8_f2f_stages_64x6_tn
fused_moe_kernel
std::enable_if<T2>(int)0&&vllm::_typeConvert<T1>::exists, void>::type vllm::fused_add_rms_norm_kernel<c10::BFloat16, (int)8>(T1 *, T1 *, const T1 *, float, int, int)
void at::native::<unnamed>::cunn_SoftMaxForward<(int)4, float, float, float, at::native::<unnamed>::SoftMaxForwardEpilogue>(T4 *, const T2 *, int)
void at::native::<unnamed>::distribution_elementwise_grid_stride_kernel<float, (int)4, void at::native::templates::cuda::uniform_and_transform<float, float, at::CUDAGeneratorImpl *, void at::native::templates::cuda::exponential_kernel<at::CUDAGeneratorImpl *>(at::TensorIteratorBase &, double, T1)::[lambda() (instance 1)]::operator ()() const::[lambda() (instance 2)]::operator ()() const::[lambda(float) (instance 1)]>(at::TensorIteratorBase &, T3, T4)::[lambda(curandStatePhilox4_32_10 *) (instance 2)], void at::native::<unnamed>::distribution_nullary_kernel<float, float, float4, at::CUDAGeneratorImpl *, void at::native::templates::cuda::uniform_and_transform<float, float, at::CUDAGeneratorImpl *, void at::native::templates::cuda::exponential_kernel<at::CUDAGeneratorImpl *>(at::TensorIteratorBase &, double, T1)::[lambda() (instance 1)]::operator ()() const::[lambda() (instance 2)]::operator ()() const::[lambda(float) (instance 1)]>(at::TensorIteratorBase &, T3, T4)::[lambda(curandStatePhilox4_32_10 *) (instance 2)], void at::native::templates::cuda::exponential_kernel<at::CUDAGeneratorImpl *>(at::TensorIteratorBase &, double, T1)::[lambda() (instance 1)]::operator ()() const::[lambda() (instance 2)]::operator ()() const::[lambda(float) (instance 1)]>(at::TensorIteratorBase &, T4, const T5 &, T6)::[lambda(int, float) (instance 1)]>(long, at::PhiloxCudaState, T3, T4)
void at::native::<unnamed>::indexSelectLargeIndex<c10::BFloat16, long, unsigned int, (int)2, (int)2, (int)-2, (bool)1>(at::cuda::detail::TensorInfo<T1, T3>, at::cuda::detail::TensorInfo<const T1, T3>, at::cuda::detail::TensorInfo<const T2, T3>, int, int, T3, T3, long)
void at::native::<unnamed>::indexSelectSmallIndex<c10::BFloat16, long, unsigned int, (int)2, (int)2, (int)-2>(at::cuda::detail::TensorInfo<T1, T3>, at::cuda::detail::TensorInfo<const T1, T3>, at::cuda::detail::TensorInfo<const T2, T3>, int, int, T3, long)
void at::native::elementwise_kernel<(int)128, (int)2, void at::native::gpu_kernel_impl_nocast<at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float>>>(at::TensorIteratorBase &, const T1 &)::[lambda(int) (instance 1)]>(int, T3)
void at::native::elementwise_kernel<(int)128, (int)2, void at::native::gpu_kernel_impl_nocast<at::native::direct_copy_kernel_cuda(at::TensorIteratorBase &)::[lambda() (instance 3)]::operator ()() const::[lambda() (instance 7)]::operator ()() const::[lambda(float) (instance 1)]>(at::TensorIteratorBase &, const T1 &)::[lambda(int) (instance 1)]>(int, T3)
void at::native::elementwise_kernel<(int)128, (int)4, void at::native::gpu_kernel_impl_nocast<at::native::direct_copy_kernel_cuda(at::TensorIteratorBase &)::[lambda() (instance 3)]::operator ()() const::[lambda() (instance 12)]::operator ()() const::[lambda(c10::BFloat16) (instance 1)]>(at::TensorIteratorBase &, const T1 &)::[lambda(int) (instance 1)]>(int, T3)
void at::native::index_elementwise_kernel<(int)128, (int)4, void at::native::gpu_index_kernel<void at::native::index_kernel_impl<at::native::OpaqueType<(int)2>>(at::TensorIteratorBase &, c10::ArrayRef<long>, c10::ArrayRef<long>)::[lambda(char *, const char *, long) (instance 1)]>(at::TensorIteratorBase &, c10::ArrayRef<long>, c10::ArrayRef<long>, const T1 &)::[lambda(int) (instance 1)]>(long, T3)
void at::native::reduce_kernel<(int)128, (int)4, at::native::ReduceOp<c10::BFloat16, at::native::func_wrapper_t<c10::BFloat16, at::native::sum_functor<c10::BFloat16, float, c10::BFloat16>::operator ()(at::TensorIterator &)::[lambda(float, float) (instance 1)]>, unsigned int, c10::BFloat16, (int)4, (int)4>>(T3)
void at::native::reduce_kernel<(int)512, (int)1, at::native::ReduceOp<float, at::native::ArgMaxOps<float>, unsigned int, long, (int)4, (int)4>>(T3)
void at::native::reduce_kernel<(int)512, (int)1, at::native::ReduceOp<float, at::native::func_wrapper_t<float, at::native::sum_functor<float, float, float>::operator ()(at::TensorIterator &)::[lambda(float, float) (instance 1)]>, unsigned int, float, (int)4, (int)4>>(T3)
void at::native::unrolled_elementwise_kernel<at::native::CUDAFunctorOnSelf_add<int>, std::array<char *, (unsigned long)2>, (int)8, TrivialOffsetCalculator<(int)1, unsigned int>, TrivialOffsetCalculator<(int)1, unsigned int>, at::native::memory::LoadWithoutCast, at::native::memory::StoreWithoutCast>(int, T1, T2, T4, T5, T6, T7)
void at::native::unrolled_elementwise_kernel<at::native::FillFunctor<int>, std::array<char *, (unsigned long)1>, (int)8, TrivialOffsetCalculator<(int)0, unsigned int>, TrivialOffsetCalculator<(int)1, unsigned int>, at::native::memory::LoadWithoutCast, at::native::memory::StoreWithoutCast>(int, T1, T2, T4, T5, T6, T7)
void at::native::unrolled_elementwise_kernel<at::native::FillFunctor<long>, std::array<char *, (unsigned long)1>, (int)8, TrivialOffsetCalculator<(int)0, unsigned int>, TrivialOffsetCalculator<(int)1, unsigned int>, at::native::memory::LoadWithoutCast, at::native::memory::StoreWithoutCast>(int, T1, T2, T4, T5, T6, T7)
void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIteratorBase &)::[lambda() (instance 3)]::operator ()() const::[lambda() (instance 3)]::operator ()() const::[lambda(int) (instance 1)], std::array<char *, (unsigned long)2>, (int)8, TrivialOffsetCalculator<(int)1, unsigned int>, TrivialOffsetCalculator<(int)1, unsigned int>, at::native::memory::LoadWithCast<(int)1>, at::native::memory::StoreWithCast<(int)1>>(int, T1, T2, T4, T5, T6, T7)
void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIteratorBase &)::[lambda() (instance 3)]::operator ()() const::[lambda() (instance 4)]::operator ()() const::[lambda(long) (instance 1)], std::array<char *, (unsigned long)2>, (int)8, TrivialOffsetCalculator<(int)1, unsigned int>, TrivialOffsetCalculator<(int)1, unsigned int>, at::native::memory::LoadWithCast<(int)1>, at::native::memory::StoreWithCast<(int)1>>(int, T1, T2, T4, T5, T6, T7)
void at::native::unrolled_elementwise_kernel<at::native::direct_copy_kernel_cuda(at::TensorIteratorBase &)::[lambda() (instance 3)]::operator ()() const::[lambda() (instance 7)]::operator ()() const::[lambda(float) (instance 1)], std::array<char *, (unsigned long)2>, (int)8, TrivialOffsetCalculator<(int)1, unsigned int>, TrivialOffsetCalculator<(int)1, unsigned int>, at::native::memory::LoadWithCast<(int)1>, at::native::memory::StoreWithCast<(int)1>>(int, T1, T2, T4, T5, T6, T7)
void at::native::vectorized_elementwise_kernel<(int)2, at::native::FillFunctor<int>, std::array<char *, (unsigned long)1>>(int, T2, T3)
void at::native::vectorized_elementwise_kernel<(int)2, at::native::FillFunctor<long>, std::array<char *, (unsigned long)1>>(int, T2, T3)
void at::native::vectorized_elementwise_kernel<(int)4, at::native::BinaryFunctor<float, float, float, at::native::binary_internal::DivFunctor<float>>, std::array<char *, (unsigned long)3>>(int, T2, T3)
void at::native::vectorized_elementwise_kernel<(int)4, at::native::FillFunctor<int>, std::array<char *, (unsigned long)1>>(int, T2, T3)
void at::native::vectorized_elementwise_kernel<(int)8, at::native::FillFunctor<c10::BFloat16>, std::array<char *, (unsigned long)1>>(int, T2, T3)
void cublasLt::splitKreduce_kernel<(int)32, (int)16, int, __nv_bfloat16, __nv_bfloat16, float, (bool)0, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, (bool)1, (bool)0, (bool)0>(cublasLt::cublasSplitKParams<T6>, const T4 *, const T9 *, T8 *, T5 *, const T6 *, const T6 *, const T10 *, const T4 *, T10 *, void *, long, T6 *, int *, T6 *, const T6 *, const T6 *, const T6 *, const T6 *)
void cublasLt::splitKreduce_kernel<(int)32, (int)16, int, float, __nv_bfloat16, float, (bool)0, __nv_bfloat16, __nv_bfloat16, __nv_bfloat16, (bool)1, (bool)0, (bool)0>(cublasLt::cublasSplitKParams<T6>, const T4 *, const T9 *, T8 *, T5 *, const T6 *, const T6 *, const T10 *, const T4 *, T10 *, void *, long, T6 *, int *, T6 *, const T6 *, const T6 *, const T6 *, const T6 *)
void cutlass::Kernel2<cutlass_80_tensorop_bf16_s16816gemm_relu_bf16_64x64_64x6_tn_align8>(T1::Params)
void cutlass::Kernel2<cutlass_80_tensorop_s16816gemm_bf16_64x64_64x6_tn_align8>(T1::Params)
void cutlass::Kernel2<cutlass_80_wmma_tensorop_bf16_s161616gemm_bf16_32x32_128x2_tn_align8>(T1::Params)
void cutlass::Kernel2<cutlass_80_wmma_tensorop_s161616gemm_bf16_32x32_128x1_tn_align8>(T1::Params)
void flash::flash_fwd_splitkv_combine_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (int)4, (bool)0, (bool)0, cutlass::bfloat16_t, Flash_kernel_traits<(int)128, (int)64, (int)128, (int)4, cutlass::bfloat16_t>>, (int)4, (int)1, (bool)1>(flash::Flash_fwd_params)
void flash::flash_fwd_splitkv_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (int)4, (bool)0, (bool)0, cutlass::bfloat16_t, Flash_kernel_traits<(int)128, (int)64, (int)128, (int)4, cutlass::bfloat16_t>>, (bool)0, (bool)0, (bool)0, (bool)0, (bool)1, (bool)0, (bool)0, (bool)0>(flash::Flash_fwd_params)
void flash::flash_fwd_splitkv_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (int)4, (bool)0, (bool)0, cutlass::bfloat16_t, Flash_kernel_traits<(int)128, (int)64, (int)128, (int)4, cutlass::bfloat16_t>>, (bool)0, (bool)0, (bool)0, (bool)0, (bool)1, (bool)0, (bool)1, (bool)0>(flash::Flash_fwd_params)
void flash::flash_fwd_splitkv_kernel<Flash_fwd_kernel_traits<(int)128, (int)64, (int)128, (int)4, (bool)0, (bool)0, cutlass::bfloat16_t, Flash_kernel_traits<(int)128, (int)64, (int)128, (int)4, cutlass::bfloat16_t>>, (bool)1, (bool)0, (bool)0, (bool)0, (bool)1, (bool)0, (bool)0, (bool)0>(flash::Flash_fwd_params)
void vllm::act_and_mul_kernel<c10::BFloat16, &vllm::silu_kernel<c10::BFloat16>, (bool)1>(T1 *, const T1 *, int)
void vllm::moe::count_and_sort_expert_tokens_kernel<int>(const T1 *, int *, int *, unsigned long)
void vllm::moe::moe_align_block_size_kernel<int>(const T1 *, int *, int *, int *, int, int, int, int, unsigned long, int *)
void vllm::moe::topkGatingSoftmax<(int)4, (int)128, (int)4, (int)16, int>(const float *, const bool *, float *, int, T5 *, int *, int, int, int)
void vllm::reshape_and_cache_flash_kernel<__nv_bfloat16, __nv_bfloat16, (vllm::Fp8KVCacheDataType)0>(const T1 *, const T1 *, T2 *, T2 *, const long *, long, long, long, long, long, int, int, int, const float *, const float *)
void vllm::rms_norm_kernel<c10::BFloat16>(T1 *, const T1 *, const T1 *, float, int, int)
void vllm::rotary_embedding_kernel<c10::BFloat16, (bool)1>(const long *, T1 *, T1 *, const T1 *, int, long, long, long, int, int, int)
```