NEMO Performance Benchmark and Profiling. May 2011
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1 NEMO Performance Benchmark and Profiling May 2011
2 Note The following research was performed under the HPC Advisory Council HPC works working group activities Participating vendors: HP, Intel, Mellanox Compute resource - HPC Advisory Council Cluster Center For more info please refer to
3 NEMO (Nucleus for European Modelling of the Ocean) NEMO is a state-of-the-art modeling framework for Oceanographic research Operational oceanography seasonal forecast Climate studies NEMO includes 4 major components The blue ocean (ocean dynamics, NEMO-OPA) The white ocean (sea-ice, NEMO-LIM) The green ocean (biogeochemistry, NEMO-TOP) The adaptative mesh refinement software (AGRIF) NEMO is used by a large community: 240 projects in 27 countries Under the CeCILL license (public license) controlled by a European Consortium between CNRS, Mercator-Ocean, UKMO and NERC NEMO is part of DEISA benchmark suite ( 3
4 Objectives The presented research was done to provide best practices File-system performance comparison MPI libraries comparisons Interconnect performance benchmarking NEMO Application profiling Understanding NEMO communication patterns The presented results will demonstrate Balanced compute environment determines application performance 4
5 Test Cluster Configuration HP ProLiant SL2x170z G6 16-node cluster Six-Core Intel 2.93 GHz CPUs Memory: 24GB per node OS: CentOS5U5, OFED InfiniBand SW stack Mellanox ConnectX-2 InfiniBand QDR adapters and switches Fulcrum based 10Gb/s Ethernet switch MPI Intel MPI 4, Open MPI 1.7, Platform MPI Compilers: Intel Compilers Application: NEMO 3.2 Libraries: Intel MKL , netcdf Benchmark workload OPA (the ocean engine), confcoef=25 5
6 About HP ProLiant SL6000 Scalable System Solution-optimized for extreme scale out ProLiant SL160z G6 ProLiant SL165z G7 Large memory -memory-cache apps Save on cost and energy -- per node, rack and data center ProLiant z6000 chassis Shared infrastructure fans, chassis, power ProLiant SL170z G6 Large storage -Web search and database apps Mix and match configurations Deploy with confidence * SPECpower_ssj June 2010, 13:28 ProLiant SL2x170z G6 Highly dense - HPC compute and web front-end apps #1 Power Efficiency* 6
7 Lustre File System Configuration Lustre Configuration 1 MDS 4 OSS (Each has 2 OST) InfiniBand based Backend storage All components are connected through InfiniBand QDR interconnect Lustre MDS/OSS OSS OSS OSS IB QDR Switch IB QDR Switch Storage Cluster Nodes 7
8 NEMO Benchmark Results File System File I/O performance is important to NEMO performance InfiniBand powered Lustre file system enables application scalability NFS over GigE doesn t meet application file I/O requirement Higher is better Open MPI over InfiniBand QDR 12-cores per node 8
9 NEMO Benchmark Results MPI Optimization Intel MPI with tuning runs 13% faster than default mode at 16 nodes -genv I_MPI_RDMA_TRANSLATION_CACHE 1 -genv I_MPI_RDMA_RNDV_BUF_ALIGN genv I_MPI_DAPL_DIRECT_COPY_THRESHOLD % Higher is better 12-cores per node 9
10 NEMO Benchmark Results MPI Libraries Intel MPI and Open MPI are faster at 16 nodes Higher is better 12-cores per node 10
11 NEMO Benchmark Results Interconnects InfiniBand enables highest performance and linear scalability for NEMO 420% faster than 10GigE and 580% faster than GigE at 16 nodes 420% 580% Higher is better 12-cores per node 11
12 NEMO MPI Profiling MPI Functions MPI point-to-point communication overhead is dominated Point-to-point: MPI_Isend/recv Collectives: MPI_Allreduce overhead increases faster after 8 nodes 12
13 NEMO MPI Profiling Message Size Most messages are small messages: <12KB 13
14 NEMO MPI Profiling Interconnects InfiniBand QDR has least communication overhead 13% of total MPI time over GigE 17% of total MPI time over 10GigE 14
15 NEMO Benchmark Summary NEMO performance benchmark demonstrates InifiniBand QDR delivers higher application performance and linear scalability 420% higher performance than 10GigE and 580% higher than GigE Intel MPI tuning can boost application performance by 13% Application has intensive file I/O operations Lustre over InfiniBand eliminates NFS bottleneck and enables application performance NEMO MPI profiling Message send/recv creates big communication overhead Most are small message used by NEMO Collectives overhead increases as cluster size scales up 15
16 Thank You HPC Advisory Council All trademarks are property of their respective owners. All information is provided As-Is without any kind of warranty. The HPC Advisory Council makes no representation to the accuracy and completeness of the information contained herein. HPC Advisory Council Mellanox undertakes no duty and assumes no obligation to update or correct any information presented herein 16 16
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