XcalableACC: Extension of XcalableMP PGAS Language Using OpenACC for Accelerator Clusters
Masahiro Nakao, Hitoshi Murai, Takenori Shimosaka, Akihiro Tabuchi, Toshihiro Hanawa, Yuetsu Kodama, Taisuke Boku, Mitsuhisa Sato · 2014
The present paper introduces the XcalableACC (XACC) programming model, which is a hybrid model of the XcalableMP (XMP) Partitioned Global Address Space (PGAS) language and OpenACC. XACC defines directives that enable programmers to mix XMP and OpenACC directives in order to develop applications that can use accelerator clusters with ease. Moreover, in order to improve the performance of stencil applications, the Omni XACC compiler provides functions that can transfer a halo region on accelerator memory via Tightly Coupled Accelerators (TCA), which is a proprietary network for transferring data directly among accelerators. In the present paper, we evaluate the productivity and the performance of XACC through implementations of the HIMENO Benchmark. The results show that thanks to the productivity improvements, XACC requires less than half the source lines of code compare to a combination of Message Passing Interface (MPI) and OpenACC, which is commonly used together as a typical programming model. As a result of these performance improvements, XACC using TCA achieved up to 2.7 times faster performance than could be obtained via the combination of OpenACC and MPI programming model using GPUDirect RDMA over InfiniBand.