In this work, we evaluate performance of a real-world image processing application that uses a cross-correlation algorithm to compare a given image with a reference one. The algorithm processes individual images represented as 2-dimensional matrices of single-precision floating-point values using operations involving dot-products and additions. We implement this algorithm on a NVIDIA Fermi GPU (Tesla 2050) using CUDA, and also manually parallelize it for the Intel Xeon X5680 (Westmere) and IBM Power7 multi-core processors. Pthreads and OpenMP with SSE and VSX vector intrinsics are used for the manually parallelized version on the multi-core CPUs. A number of optimizations were performed for the GPU implementation on the Fermi, including blocking for Fermi’s configurable on-chip memory architecture. Experimental results illustrate that on a single multi-core processor, the manually parallelized versions of the correlation application perform only a small order of factor slower than the CUDA version executing on the Fermi – 1.005s on Power7, 3.49s on Intel X5680, and 465ms on Fermi. On a two-processor Power7 system, performance approaches that of the Fermi (650ms), while the Intel version runs in 1.78s. These results conclusively demonstrate that performance of the GPU memory subsystem is critical to effectively harness its computational capabilities. For the correlation application, a significantly higher amount of effort was put into developing the GPU version when compared to the CPU ones (several days against few hours). Our experience presents compelling evidence that performance comparable to that of GPUs can be achieved with much greater productivity on modern multi-core CPUs.
By: Rajesh Bordawekar; Uday Bondhugula; Ravi Rao
Published in: RC25033 in 2010
LIMITED DISTRIBUTION NOTICE:
This Research Report is available. This report has been submitted for publication outside of IBM and will probably be copyrighted if accepted for publication. It has been issued as a Research Report for early dissemination of its contents. In view of the transfer of copyright to the outside publisher, its distribution outside of IBM prior to publication should be limited to peer communications and specific requests. After outside publication, requests should be filled only by reprints or legally obtained copies of the article (e.g., payment of royalties). I have read and understand this notice and am a member of the scientific community outside or inside of IBM seeking a single copy only.
Questions about this service can be mailed to email@example.com .