Hybrid Communication with TCA and InfiniBand on a Parallel Programming Language XcalableACC for GPU Clusters - Odajima, Tetsuya; Boku, Taisuke; Hanawa, Toshihiro; Murai, Hitoshi; Nakao, Masahiro; Tabuchi, Akihiro; Sato, Mitsuhisa (Proceedings / IEEE International Conference on Cluster Computing, 2015)
For the execution of parallel HPC applications on GPU-ready clusters, high communication latency between GPUs over nodes will be a serious problem on strong scalability. To reduce the communication latency between GPUs, we proposed the Tightly Coupled Accelerator (TCA) architecture and developed the PEACH2 board as a proof-of-concept interconnection system for TCA. Although PEACH2 provides very low communication latency, there are some hardware limitations due to its implementation depending on PCIe technology, such as the practical number of nodes in a system which is 16 currently named sub-cluster. More number of nodes should be connected by conventional interconnections such as InfiniBand, and the entire network system is configured as a hybrid one with global conventional network and local high-speed network by PEACH2. For ease of user programmability, it is desirable to operate such a complicated communication system at the library or language level (which hides the system). In this paper, we develop a hybrid interconnection network system combining PEACH2 and InfiniBand, and implement it based on a high-level PGAS language for accelerated clusters named XcalableACC (XACC). A preliminary performance evaluation confirms that the hybrid network improves the performance based on the Himeno benchmark for stencil computation by up to 40%, relative to MVAPICH2 with GDR on InfiniBand. Additionally, Allgather collective communication with a hybrid network improves the performance by up to 50% for networks of 8 to 16 nodes. The combination of local communication, supported by the low latency of PEACH2 and global communication supported by the high bandwidth and scalability of InfiniBand, results in an improvement of overall performance.