Axel: a heterogeneous cluster with FPGAs and GPUs

Authors:
Kuen Hung Tsoi;Wayne Luk
Affiliations:
Imperial College London, London, United Kingdom;Imperial College London, London, United Kingdom
Venue:
Proceedings of the 18th annual ACM/SIGDA international symposium on Field programmable gate arrays
Year:
2010

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Abstract

This paper describes a heterogeneous computer cluster called Axel. Axel contains a collection of nodes; each node can include multiple types of accelerators such as FPGAs (Field Programmable Gate Arrays) and GPUs (Graphics Processing Units). A Map-Reduce framework for the Axel cluster is presented which exploits spatial and temporal locality through different types of processing elements and communication channels. The Axel system enables the first demonstration of FPGAs, GPUs and CPUs running collaboratively for N-body simulation. Performance improvement from 4.4 times to 22.7 times has been achieved using our approach, which shows that the Axel system can combine the benefits of the specialization of FPGA, the parallelism of GPU, and the scalability of computer clusters.