Compiler-directed scratchpad memory data transfer optimization for multithreaded applications on a heterogeneous many-core architecture

Abstract

The heterogeneous many-core architecture plays an important role in the fields of high-performance computing and scientific computing. It uses accelerator cores with on-chip memories to improve performance and reduce energy consumption. Scratchpad memory (SPM) is a kind of fast on-chip memory with lower energy consumption compared with a hardware cache. However, data transfer between SPM and off-chip memory can be managed only by a programmer or compiler. In this paper, we propose a compiler-directed multithreaded SPM data transfer model (MSDTM) to optimize the process of data transfer in a heterogeneous many-core architecture. We use compile-time analysis to classify data accesses, check dependences and determine the allocation of data transfer operations. We further present the data transfer performance model to derive the optimal granularity of data transfer and select the most profitable data transfer strategy. We implement the proposed MSDTM on the GCC complier and evaluate it on Sunway TaihuLight with selected test cases from benchmarks and scientific computing applications. The experimental result shows that the proposed MSDTM improves the application execution time by 5.49$$\times$$ × and achieves an energy saving of 5.16$$\times$$ × on average.

A Novel Prediction Model for Compiler Optimization with Hybrid Meta-Heuristic Optimization Algorithm

“…A variety of runtime system settings were then modified at constructing time depending on the outcomes of these investigations. Xiaohan et al [4] presented a compiler-directed MSDTM to improve data transmission in a heterogeneous many-core system. Further, compile-time analysis was employed for classification.…”