Copyrights to these papers may be held by the publishers. The download files are preprints. It is understood that all persons copying this information will adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.
Qiuling Zhu, H. E. Sumbul, F. Sadi, James C. Hoe, Lawrence Pileggi and Franz Franchetti (Proc. High Performance Extreme Computing (HPEC), pp. 1-6, 2013)
Accelerating Sparse Matrix-Matrix Multiplication with 3D-Stacked Logic-in-Memory Hardware
Published paper (link to publisher)
Bibtex
This paper introduces a 3D-stacked logic-in-memory (LiM) system to accelerate the processing of sparse matrix data that is held in a 3D DRAM system. We build a customized content addressable memory (CAM) hardware structure to exploit the inherent sparse data patterns and model the LiM based hardware accelerator layers that are stacked in between DRAM dies for the efficient sparse matrix operations. Through silicon vias (TSVs) are used to provide the required high inter-layer bandwidth. Furthermore, we adapt the algorithm and data structure to fully leverage the underlying hardware capabilities, and develop the necessary design framework to facilitate the design space evaluation and LiM hardware synthesis. Our simulation demonstrates more than two orders of magnitude of performance and energy efficiency improvements compared with the traditional multithreaded software implementation on modern processors.
Keywords: Acceleration, Hardware, 3D-stacked, Logic-in-memory