Hierarchical Read/Write Analysis for Pointer-Based OpenCL Programs on RRAM

• Published in: 2017 46th International Conference on Parallel Processing Workshops (ICPPW) pp. 45 - 52
• Main Authors: Lin-Ya Yu, Shao-Chung Wang, Jenq-Kuen Lee
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.08.2017
• Subjects: Algorithm design and analysis; Compiler; Computational modeling; Hardware; hierarchical read/write analysis; Kernel; LLVM; OpenCL; pointer analysis; Program processors; Programming; Random access memory
• ISSN: 1530-2016; 2375-530X
• DOI: 10.1109/ICPPW.2017.20

Heterogeneous computing platforms containing a wide range of computing resources from CPUs to specialized hardware accelerators is the trend today resulting from the physical limitations on processors speed and the increasing demand for computing performance. Hence many optimization strategies are studied to get better throughput and lower energy consumption in heterogeneous systems. Various memory technologies such as DRAM, STT-RAM, and RRAM are also developed to help reach the goal. Meanwhile OpenCL is an open programming language standard for programmers to write programs on these hardware accelerators in a heterogeneous system. In this paper, a new static analysis technique, based on OpenCL programming languages can determine read/write characteristics of instances within the program is presented. We consider the computing configuration with both DRAM and RRAM. We try to answer the question of which variables stored on RRAM will benefit energy efficiency with compiler analysis. Our compiler scheme based on Memory SSA enables the analysis to cover pointer-based programs. Our evaluation demonstrates that the read/write information obtained from the proposed design has great potential to achieve high energy-savings. The average error distance of our proposed scheme is 0.3548. In addition, compared to the baseline system, the read/write information help gain average 37.06% energy-saving per kernel.