Abstract: Numerous studies have proposed hardware architectures to accelerate sparse matrix multiplication, but these approaches often incur substantial area and power overhead, significantly ...

Abstract: Sparse linear algebra is essential in many domains due to reduced computation and efficient memory usage. However, the irregularity of sparse data poses challenges for conventional software ...

* Program re-ordering for improved L2 cache hit rate. * Automatic performance tuning. # Motivations # Matrix multiplications are a key building block of most modern high-performance computing systems.

点击上方“Deephub Imba”,关注公众号,好文章不错过 !做过 GPU kernel 优化的人对以下编程模型肯定不会陌生：写一个 CUDA kernel分发到流式多处理器（SM）上执行，缓存层次结构自行负责数据搬运。而TPU ...

Deep learning has been successfully applied in the field of medical diagnosis, and improving the accurate classification of ...