2 个仓库
Specialized device-side kernels written for non-GPU accelerators like NPUs or MLUs.
Distinct from GPU Kernel Programming: Focuses specifically on non-GPU accelerator programming (MLU/NPU) rather than general graphics hardware kernels.
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AISystem is a comprehensive AI full-stack infrastructure project covering the entire pipeline from AI chip architecture to high-level training frameworks. It encompasses the development of AI compiler frameworks, inference engines, and distributed training orchestrators designed to coordinate workloads across a heterogeneous compute stack of CPUs, GPUs, and NPUs. The project focuses on the deep integration of software and hardware, employing software-hardware co-design to align tensor layouts with physical memory structures. It provides specialized capabilities for accelerating Transformer mo
Writes device-side kernels using C++ or Python to manage task partitioning and synchronization.
该项目是一个全面的教育资源和课程,专注于完整机器学习软件和硬件栈的设计与实现。它作为架构机器学习系统的技术参考,涵盖从低级编程接口到大规模部署基础设施的各个方面。 该项目提供关于多个专业领域的教学指导,包括通过中间表示和图优化开发 AI 编译器。它涵盖了跨 GPU 集群进行分布式训练所需的架构模式,以及为优化专用芯片上的工作负载而进行的硬件加速器编程。 该资源还详细介绍了生产环境的模型服务框架实现以及强化学习流水线的构建。其范围扩展到 ML 系统的核心组件,例如自动微分、张量抽象和 GPU 资源的编排。
Teaches the implementation of high-performance kernels for specialized AI accelerators and NPUs.