A hybrid approach to cache management in heterogeneous CPU-FPGA platforms

Abstract

Heterogenous computing is gaining increasing attention due to its promise of high performance with low power. Shared coherent cache based CPU-FPGA platforms, like Intel HARP, are a particularly promising example of such systems with enhanced efficiency and high flexibility. In this work, we propose a hybrid strategy that relies on both static analysis of applications and dynamic control of cache based on static analysis to minimize the contention on the FPGA cache in the emerging CPU-FPGA platforms with shared coherent caches. In the static analysis, we analyze memory access patterns of the accelerated kernels on FPGA using reuse distance theory and generate kernel characteristics called Key values. Thereafter, a dynamic scheme for cache bypassing and partitioning control based on these Key values is developed to increase the cache hit rate and improve the performance. We validate our proposed strategy using a system-level architectural simulator for CPU-FPGA heterogeneous computing systems. Experiments show that the proposed strategy can increase the cache hit rate by 22.90% on average and speed up the application by up to 12.52% with negligible area overhead.