unifex::static_thread_pool workers; ex::sender auto accept_and_process_requests() { return ex::on(low_latency.get_scheduler(), accept_request()) | ex::transfer(workers.get_scheduler()) | ex::then([](auto process_request(request_t); extern unifex::static_thread_pool low_latency; extern unifex::static_thread_pool workers; unifex::task accept_and_process_requests() { while (true) { auto request = co_await co_await ex::on(low_latency.get_scheduler(), accept_request()); co_await ex::on(workers.get_scheduler(), process_request(request)); } } Or write it as a coroutine.17 Schedulers produce senders

on the device, • Callable from the device only. https://docs.nvidia.com/cuda/cuda-c-programming-guide/ index.html#function-declaration-specifiers 36 |The __host__ execution space specifier declares case the function is compiled for the host only. https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#host Execution Space Specifiers 37 |__host__ __device__ void _add(std::size_t n, float

这样就可以和标准库优化过的 memset 一 样快了。 Intel Intrinsics Guide • _mm 系列指令出自 头文件。 • 指令的文档可以看这个网站： • https://www.intel.com/content/www/us/en/docs/intrinsics-guide/index.html • 里面有详细说明每个指令对应的汇编，方便理解的伪代码，延迟和花费的时钟周期等。

add_executable 里直接加你 的 .cu 文件，和 .cpp 一样。 https://www.nvidia.cn/docs/IO/51635/NVIDIA_CUDA_Programming_Guide_1.1_chs.pdf CUDA 编译器兼容 C++17 • CUDA 的语法，基本完全兼容 C++ 。包括 C+ +17 新特性，都可以用。甚至可以把任何一个 C++ 项目的文件后缀名全部改成 ， acosf ， fmodf ， fabsf ， fminf ， fmax f 。 https://docs.nvidia.com/cuda/cuda-c-best-practices-guide/index.html#math-libraries 稍微快一些，但不完全精确的 __sinf • 两个下划线的 __sinf 是 GPU intrinstics ，精度相当于 GLSL 里的那种。

experienceCoaching JourneyCoaching“I don’t do anything!”Coach • Bulldozer – Remove impediments • Shepherd – Guide back to agile principles • Servant Leader – Serve the team, not you • Performance Guardian – Facilitate

operator: kubectl apply -f clickhouse-operator-install.yaml • Хочу просто попробовать Quick Start Guide kubectl apply -f https://raw.githubusercontent.com/Altinity/clickhouse-operator/master/manifests/oper

https://github.com/parallel101/course CUDA 纹理对象 https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#texture-and-surface-memory CUDA 多维数组：封装 • cudaMalloc3DArray 用于分配一个三维数组。 各维度上的大小通过 cudaExtent

pace 💡 Side-by-side minor Visual Studio 2022 toolsets (14.30, 14.31, etc.) Porting and Upgrading Guide: https://aka.ms/cpp/upgrade Visual Studio Agenda 1. Conformance 2. Code Safety 3. Cross-platform