高层工具(High-Level & Productive)包含libcu++提供 C++ 标准库扩展,如cuda::std::variant和cuda::std::optional,便于使用容器和抽象化的功能。以及Thrust提供 CPU/GPU 并行算法,用于快速开发高层算法和数据处理。 中间层工具(中等抽象层次)包含迭代器(Fancy Iterators)如cuda::std::span和cuda::std::mdspan,用于...
Proteins/pytorch/aten/src/ATen/core/IListRef_inl.h: In static member function 'static c10::detail::IListRefConstRefat::OptionalTensorRef c10::detail::IListRefTagImpl<c10::IListRefTag::Boxed, at::OptionalTensorRef>::iterator_get(const c10::List<std::optionalat::Tensor >::const_iterator&)...
Instead, it simply returns a std::vector<std::optional<cudaStream_t>>, which is a vector of size equal to the number of messages on the input port. Each value in the vector corresponds to the cudaStream_t specified by the message (or std::nullopt if no stream ID is found). Note ...
std::optional<bool> use_trt_causal_attention = std::nullopt; void SetTrtFusedKernel(bool causal, bool enable_trt_flash_attention, int sequence_length); void Print(const char* operator_name, const std::string& node_name, bool is_float16, bool is_bfloat16) const; }; class AttentionKernel...
Specifying a stream for a kernel launch or host-device memory copy is optional; you can invoke CUDA commands without specifying a stream (or by setting the stream parameter to zero). The following two lines of code both launch a kernel on the default stream. ...
// Print the result (optional) for (int i = 0; i < N; ++i) { for (int j = 0; j < N; ++j) { std::cout << C[i][j] << " "; } std::cout << std::endl; } return 0; } [参考链接] 1.紫气东来:CUDA(一):CUDA 编程基础 ...
(cuda-gdb) cuda thread (15) [Switching focus to CUDA kernel 1, grid 2, block (8,0,0), thread (15,0,0), device 0, sm 1, warp 0, lane 15] 374 int totalThreads = gridDim.x * blockDim.x; The parentheses for the block and thread arguments are optional. (cuda-gdb) cuda ...
Ubuntu18.04 + cuda (+ Optional Pytorch) Step1: 检查硬件和系统 检查版本和类型:ubuntu-drivers devices$ sudo ubuntu-drivers listnvidia-driver-390 $ ubuntu-drivers devices== /sys/devices/pci0000:00/0000:00:01.0/0000:01:00.0 ==modalias : pci:v000010DEd00001B06sv00001458sd0000374Cbc03sc00i00ve...
Ubuntu18.04 + cuda (+ Optional Pytorch) Step1: 检查硬件和系统 检查版本和类型:ubuntu-drivers devices $ sudo ubuntu-drivers list nvidia-driver-390 $ ubuntu-drivers devices == /sys/devices/pci0000:00/0000:00:01.0/0000:01:00.0 == modalias : pci:v000010DEd00001B06sv00001458sd0000374Cbc03sc00...
void* device_memory_resource::allocate(std::size_t bytes, cuda_stream_view s)—Returns a pointer to an allocation of the requested size in bytes. void device_memory_resource::deallocate(void* p, std::size_t bytes, cuda_stream_view s)—Reclaims a previous allocation of size bytes pointed...