11734

BigKernel — High Performance CPU-GPU Communication Pipelining for Big Data-style Applications

R. Mokhtari, M. Stumm
University of Toronto, Toronto, Ontario, Canada
@article{mokhtaribigkernel,

   title={BigKernel—High Performance CPU-GPU Communication Pipelining for Big Data-style Applications},

   author={Mokhtari, Reza and Stumm, Michael}

}

Download Download (PDF)   View View   Source Source   

2796

views

GPUs offer an order of magnitude higher compute power and memory bandwidth than CPUs. GPUs therefore might appear to be well suited to accelerate computations that operate on voluminous data sets in independent ways; e.g., for transformations, filtering, aggregation, partitioning or other ”Big Data” style processing. Yet experience indicates that it is difficult, and often error-prone, to write GPGPU programs which efficiently process data that does not fit in GPU memory, partly because of the intricacies of GPU hardware architect ure and programming models, and partly because of the limited bandwidth available between GPUs and CPUs. In this paper, we propose BigKernel, a scheme that provides pseudo-virtual memory to GPU applications and is implemented using a 4-stage pipeline with automated prefetching to (i) optimize CPU-GPU communication and (ii) optimize GPU memory accesses. BigKernel simplifies the programming model by allow ing programmers to write kernels using arbitrarily large data structures that can be partitioned into segments where each segment is operated on independently; these kernels are transformed into BigKernel using straight-forward compiler transformations. Our evaluation on six data-intensive benchmarks shows that BigKernel achieves an average speedup of 1.7 over state-of-the-art double-buffering techniques and an average speedup of 3.0 over corresponding multi-threaded CPU implementations.
VN:F [1.9.22_1171]
Rating: 4.7/5 (3 votes cast)
BigKernel — High Performance CPU-GPU Communication Pipelining for Big Data-style Applications, 4.7 out of 5 based on 3 ratings

* * *

* * *

Follow us on Twitter

HGPU group

1943 peoples are following HGPU @twitter

Like us on Facebook

HGPU group

442 people like HGPU on Facebook

HGPU group © 2010-2016 hgpu.org

All rights belong to the respective authors

Contact us: