Analyzing Performance Improvements and Energy Savings in Infiniband Architecture using Network Compression
Paper in proceedings, 2014

One of the greatest challenges in HPC is total system power and energy consumption. Whereas HPC interconnects have traditionally been designed with a focus on bandwidth and latency, there is an increasing interest in minimising the interconnect's energy consumption. This paper complements ongoing efforts related to power reduction and energy proportionality, by investigating the potential benefits from MPI data compression. We apply lossy compression to two common communication patterns in HPC kernels, in conjunction with recently introduced InfiniBand (IB) power saving modes. The results for the Alya CG kernel and Gromacs PME solver kernels show improvements in both performance and energy. While performance improvements are strongly influenced and changable depending on the type of communication pattern, energy savings in IB links are more consistent and proportional to achievable compression rates. We estimated an upper bound for link energy savings of up to 71% for the ALYA CG kernel, while for the Gromacs PME solver we obtained savings up to 63% compared to nominal energy when compression rate of 50% is used. We conclude that lossy compression is not always useful for performance improvements, but that it does reduce average IB link energy consumption

Data Compression

MPI Performance

Parallel Applications

Supercomputing

Network Energy Savings

Author

B. Dickov

Centro Nacional de Supercomputacion

Polytechnic University of Catalonia

Miquel Pericas

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

P.M. Carpenter

Centro Nacional de Supercomputacion

N. Navarro

Centro Nacional de Supercomputacion

Polytechnic University of Catalonia

Sally A McKee

Polytechnic University of Catalonia

Centro Nacional de Supercomputacion

Computer Architecture and High Performance Computing (SBAC-PAD), 2014 IEEE 26th International Symposium on

1550-6533 (ISSN)

73-80

Areas of Advance

Information and Communication Technology

Subject Categories

Computer Systems

DOI

10.1109/SBAC-PAD.2014.27

ISBN

9781479969043

More information

Latest update

3/29/2018