Efficient Collective Communication on Heterogeneous Networks of Workstations

• Authors: Mohammad Banikazemi;Vijay Moorthy;Dhabaleswar K. Panda
• Venue: ICPP '98 Proceedings of the 1998 International Conference on Parallel Processing
• Year: 1998

Networks of Workstations (NOW) have become an attractive alternative platform for high performance computing. Due to the commodity nature of workstations and interconnects and due to the multiplicity of vendors and platforms, the NOW environments are being gradually redefined as Heterogeneous Networks of Workstations (HNOW) environments. This paper presents a new framework for implementing collective communication operations (as defined by the Message Passing Interface (MPI) standard) efficiently for the emerging HNOW environments. We first classify different types of heterogeneity in HNOW and then focus on one important characteristic: communication capabilities of workstations. Taking this characteristic into account, we propose two new approaches (Speed-Partitioned Ordered Chain (SPOC) and Fastest-Node First (FNF)) to implement collective communication operations with reduced latency. We also investigate methods for deriving optimal trees for broadcast and multicast operations. Generating such trees is shown to be computationally intensive. It is shown that the FNF approach, in spite of its simplicity, can deliver performance within 1% of the performance of the optimal trees. Finally, these new approaches are compared with the approach used in the MPICH implementation on experimental as well as on simulated testbeds. On a 24-node existing HNOW environment with SGI workstations and ATM interconnection, our approaches reduce the latency of broadcast and multicast operations by a factor of up to 3.5 compared to the approach used in the existing MPICH implementation. On a 64-node simulated testbed, our approaches can reduce the latency of broadcast and multicast operations by a factor of up to 4.5. Thus, these results demonstrate that there is significant potential for our approaches to be applied towards designing scalable collective communication libraries for current and future generation HNOW environments.