mtGEMM: An Efficient GEMM Library for Modern Multi-Core DSPs

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Authors: Jianbin Fang, Kainan Yu, Peng Zhang, Dezun Dong, Xinxin Qi, Xingyu Hou, Ruibo Wang, Kai Lu
Cited by: 1
References: 25

Abstract

The General Matrix Multiplication (GEMM) is a crucial subprogram in high-performance computing (HPC). With the increasing importance of power and energy consumption, modern Digital Signal Processors (DSPs) are being integrated into general-purpose HPC systems. However, due to architecture disparities, traditional optimizations for CPUs and GPUs are not easily applicable to modern DSPs. This paper shares our experience of optimizing the GEMM operation using a CPU-DSP platform as a case study. Our work employs a set of strategies to improve the performance and scalability of GEMM. These strategies focus on developing micro-kernels based on heterogeneous on-chip memory, addressing the memory access bottleneck in multi-core parallelism, and facilitating efficient transpose-GEMM. These approaches, collectively referred to as an efficient and practical library (a.k.a.mtGEMM), maximize computational capabilities and bandwidth utilization of multi-core DSPs, while achieving high performance for variously-shaped GEMMs. Our experimental results demonstrate thatmtGEMMcan attain between 92% and 96% of the hardware peak, with the multi-core scalability being almost linear.

Fields of Study & Subjects

Parallel Computing and Optimization Techniques Numerical Methods and Algorithms Low-power high-performance VLSI design

Publication details

Journal / source
IEEE Transactions on Parallel and Distributed Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Volume
37
Issue
4
Pages
905–919
Publication date
12 February 2026