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HPC Application Performance

Study on 4S Servers

by Ranga Balimidi, Ashish K. Singh, and Ishan Singh

What can you do with a big bad 4-socket machine with 60 cores with up to 6TB memory in HPC? To help answer that

question, we conducted a performance study using several benchmark suites such as HPL, STREAM, WRF and

Fluent. This blog describes some of our results that help illustrate the possibilities. The server that we used for this

study is the Dell PowerEdge R920. This server supports the family of processors in the Intel architecture code named

Ivy Bridge EX.

The server configuration table outlines the configuration details used for this study as well as the configurations from

a previous study performed in June 2010 with the previous generation of technology. We use these two systems to

compare performance across technology refresh.

Server Configuration

Power Edge R920 Hardware

Processors 4 x Intel Xeon E7-4870v2 @ 2.3GHz (15 cores) 30M

cache 130W

Memor

512 GB =32 * 16GB 1333MHz RDIMMs

PowerEdge R910 Hardware

Processor 4 x Intel Xeon X7550 @ 2.00GHz (8 cores) 18M cache

130W

Memor

128GB = 32 * 4GB 1066MHz RDIMMs

Software and Firmware for PowerEdge R920

Operating System Red Hat Enterprise Linux 6.5 (kernel version 2.6.32-431.el6

x86

64)

Intel Compile

Version 14.0.2

Intel MKL Version 11.1

Intel MPI Version 4.1

BIOS Version 1.1.0

BIOS Settings System Profile set to Performance

(Lo

ical Processor disabled, Node Interleave disabled)

Benchmarks & Applications for PowerEdge R920

HPL v2.1, From Intel MKL v11.1, Problem size 90% of total

memor

Summary of content (7 pages)

PAGE 1
HPC Application Performance Study on 4S Servers by Ranga Balimidi, Ashish K. Singh, and Ishan Singh What can you do with a big bad 4-socket machine with 60 cores with up to 6TB memory in HPC? To help answer that question, we conducted a performance study using several benchmark suites such as HPL, STREAM, WRF and Fluent. This blog describes some of our results that help illustrate the possibilities. The server that we used for this study is the Dell PowerEdge R920.
PAGE 2
Stream WRF Fluent v5.10, Array Size 1800000000, Iterations 100 v3.5.1, Input Data Conus 12K, Netcdf-4.3.1.1 v15, Input Data: eddy_417k, truck_poly_14m, sedan_4m, aircraft_2m Results and Analysis For this study, we compared the two servers across the four benchmarks described below. The aim of this comparison is to show the generation-over-generation changes in this four socket platform. Each server was configured with the optimal software and BIOS configurations at the time of the measurements.
PAGE 3
The graph also plots the local bandwidth and remote memory bandwidth. Local memory bandwidth is measured by binding processes to a socket and accessing only memory local to that socket (NUMA enabled, same NUMA node). Remote memory bandwidth is measured by binding processes to one socket and only accessing memory that is remote to that socket (remote NUMA node) where it has to go through QPI link to access this memory.
PAGE 4
HPL yielded 4.67x sustained performance improvement in this study. This is primarily due to the substantial increase in the number of cores, increase in the FLOP/cycle of the processor and the overall improvement in the processor architecture. WRF The Weather Research and Forecasting (WRF) Model is a numerical weather prediction system designed to serve atmospheric research and weather forecasting needs.
PAGE 5
We have taken the average time step as the metric to measure WRF performance. We used Conus 12km data set for this application. In the graph above we've plotted the WRF performance results from this study relative to results from the previous generation. Since there is an increase in number of cores on Intel E7-4870 v2 processor, we have scaled up WRF to 60 cores and observed significant performance increase while scaling.
PAGE 6
We've used four input data sets for Fluent. We've considered “Solver Rating” (higher is better) as the performance metric for these test cases. For all the test cases, Fluent scaled very well with 100% CPU utilization. Comparing generation-to-generation, for 32 core-to-core comparisons we observed the R920 performance results are approximately 2x better over the previous generation in all the test cases. When it comes to server-to-server comparison using all available cores, it performs 33.5x better.
PAGE 7
$cat ~/.fluent (define (set-affinity argv) (display "set-affinity disabled")) Conclusion The PowerEdge R920 server outperforms its previous generation server in both benchmarks and applications comparisons studied in this exercise. The platform has its advantage over the previous generation platform in terms of latest processor support, increased memory speed and capacity support, and overall system architecture improvements.