Multithreaded Chunking for Hybrid Cores in Modern Deduplication

Abstract

The fast development of Graphics Processing Unit (GPU) leads to the popularity of General-purpose usage of GPU (GPGPU). So far, most modern computers are CPU-GPGPU heterogeneous architecture and CPU is used as host processor. In this work, we built a hybrid multithread chunking prototype system to coordinate the computing capabilities. The prototype system is able to exploit the hardware organization of the CPU-GPGPU heterogeneous architecture computer and determine which device should be used to chunk the file to accelerate the content based file chunking operation of deduplication. We built rules for the system to choose which device should be used to chunk file and also found the optimal choice of other related parameters of both CPU and GPGPU subsystem like segment size and block dimension. This prototype was implemented and tested. The result of using GTX460(336 cores) and Intel i5(four cores) shows that this system can increase the chunking speed 63% compared to use GPGPU alone and 80% compared to use CPU alone.