FCUDA: Enabling efficient compilation of CUDA kernels onto FPGAs

— As growing power dissipation and thermal effects disrupted the rising clock frequency trend and threatened to annul Moore’s law, the computing industry has switched its route to higher performance through parallel processing. The rise of multi-core systems in all domains of computing has opened the door to heterogeneous multi-processors, where processors of different compute characteristics can be combined to effectively boost the performance per watt of different application kernels. GPUs and FPGAs are becoming very popular in PC-based heterogeneous systems for speeding up compute intensive kernels of scientific, imaging and simulation applications. GPUs can execute hundreds of concurrent threads, while FPGAs provide customized concurrency for highly parallel kernels. However, exploiting the parallelism available in these applications is currently not a push-button task. Often the programmer has to expose the application’s fine and coarse grained parallelism by using special A...

• Type: Conference
• Year: 2009
• Where: SASP
• Authors: Alexandros Papakonstantinou, Karthik Gururaj, John A. Stratton, Deming Chen, Jason Cong, Wen-mei W. Hwu
• Keywords: CUDA, CUDA Programming Model, FPGA, Hardware, SASP 2009