2 个仓库
Awesome GitHub RepositoriesKernel-to-Template Bindings
Associates a kernel function with a hardware-aware template so generated configurations apply to that specific kernel.
Distinct from Pure Function Kernels: Distinct from Pure Function Kernels: binds kernel functions to hardware templates for configuration generation, not just compiling pure functions.
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Awesome Kernel-to-Template Bindings GitHub Repositories
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- tile-ai/tilelang
tile-ai/tilelang
5,226在 GitHub 上查看TileLang is a Python-embedded domain-specific language compiler that JIT-compiles and autotunes GPU kernels. It uses a tile-based DSL, automatic software pipelining, and parallel autotuning to generate optimized GPU kernels at runtime. It supports tensor core operations with Pythonic syntax, automatic memory management, and thread mapping. The compiler searches over tile sizes, thread counts, and scheduling policies, compiling and benchmarking candidates in parallel to find the fastest kernel. It also caches compiled binaries and tuning results to disk for reuse across sessions. TileLang inc
Binds kernel functions to hardware-aware templates for targeted configuration generation.
Python - answerdotai/gpu.cpp
AnswerDotAI/gpu.cpp
3,981在 GitHub 上查看gpu.cpp 是一个轻量级的 C++ 库，用于跨不同硬件供应商和操作系统执行底层通用 GPU 计算。它作为一个便携式 GPU 包装器、内核编排器和张量管理系统，利用 WebGPU 规范来抽象设备初始化、缓冲区传输和计算着色器调度。 该库提供了一个框架，用于从着色器代码定义计算内核，并管理其异步调度与同步。它支持跨平台计算着色器的执行，并通过标准化的图形处理器规范编排 GPU 任务。 该系统处理 GPU 内存的全生命周期，包括多维张量的分配、通过暂存缓冲区在主机与设备之间的双向数据移动，以及防止内存泄漏的资源跟踪。它还支持用于创建非所有权内存段视图的张量切片，并包含系统消息日志记录和严重性过滤工具。
Maps buffers and tensors to specific indices so a GPU kernel can access them during execution.
C++
