Sun Blade X6275 Server Modules Excel on MCAE Applications


(As of Tuesday, 17 November 2009)

Sixteen of Oracle’s dual-node Sun Blade X6275 server modules, powered by two Intel Xeon X5570 processors, formed a cluster that was interconnected via integrated InfiniBand QDR Host Channel Adapters (HCA) and Quad Data Rate Switched Network Express Modules (QNEM), and housed in Oracle’s Sun Blade 6048 chassis. Since each Sun Blade X6275 server module has two full-function compute nodes inside, the total number of processing cores in the cluster was 256. The Sun Blade X6275 cluster outpaced competing SGI Altix ICE system on two popular MCAE applications—FLUENT from ANSYS Inc. and RADIOSS from Altair.

Sixteen dual-node Sun Blade X6275 server modules, running 64-bit SUSE Linux (SLES10 SP2) OS across 256 logical CPUs, demonstrated world record performance using the largest available model of FLUENT 12.0 benchmark. Truck_111M model has around 111 million cells and models external air flow over a truck body.


ANSYS's FLUENT software solves fluid flow problems, and is based on a numerical technique called computational fluid dynamics (CFD), which is used in the automotive, aerospace, and consumer products industries. The FLUENT 12 benchmark test suite consists of seven models that are well suited for multi-node clustered environments and representative of modern engineering CFD clusters. Vendors benchmark their systems with the principal objective of providing comparative performance information for FLUENT software that, among other things, depends on compilers, optimization, interconnect, and the performance characteristics of the hardware.


Fluent 12.0 Benchmark
Results are "Ratings" (bigger is better)
Rating is number of sequential runs of test case possible in 1 day 86,400/(Total Elapsed Run Time in Seconds)

System Core Model: Truck_111M
Sun Blade X6275 64 64.6
SGI ALTIX ICE 8200 IP95 64 59.8
Sun Blade X6275 128 129.6
SGI ALTIX ICE 8200 IP95 128 120.8
Sun Blade X6275 256 240.0
SGI ALTIX ICE 8200 IP95 256 238.9

The same cluster comprised of sixteen dual-node Sun Blade X6275 server modules running 64-bit SUSE Linux (SLES10 SP2) across 256 logical CPUs demonstrated world record performance on RADIOSS benchmark.

Altair's RADIOSS is a next-generation finite element solver for structural analysis and is often used for high-speed impact simulations in automotive and aerospace industries. To demonstrate the performance of RADIOSS, Altair has come up with a suite of benchmarks that include four automotive crash models based on real data. For the 256 rank configuration running the largest available model Taurus_v_Taurus 1.8M) that simulates the frontal crash of two identical cars, the Sun Blade X6275 cluster outperformed the SGI Altix ICE by over 30%, while on the second largest model (Taurus_Frontal 835K), the cluster outperformed SGI by over 40%.

System Ranks Taurus_v_Taurus 1.8M Taurus_Frontal 835K Neon_1M 1.06M Neon_300K 276K
Sun Blade X6275 2.93GHz, 32 nodes, QDR 256 3616 2505 1647  
SGI Altix ICE 8200 IP95 2.93GHz, 32 nodes, DDR 256 4745 3559 1672 310
Sun Blade X6275 2.93GHz, 16 nodes, QDR 128 5769 3045 2268 348
SGI Altix ICE 8200 IP95 2.93GHz, 16 nodes, DDR 128 6308 5033 2422 360
Sun Fire X2270 2.93GHz, 8 nodes, QDR 64 9929 5557 3896 539
SGI Altix ICE 8200 IP95 2.93GHz, 8 nodes, DDR 64 10015 6181 4088 584
Sun Fire X2270 2.93GHz, 4 nodes, QDR 32 16518 9155 7428 1015
SGI Altix ICE 8200 IP95 2.93GHz, 4 nodes, DDR 32 17336 10120 7574 1017

The above tables point out that the Sun Blade cluster maintained very good average scalability efficiency as the system grew in size and relied on a high performance Lustre file system to expedite the necessary data. Deploying shared file systems in clustered environments with large data sets often results in an additional performance boost due to lowered access times to files shared by all nodes.

These stellar results highlight the performance of uniquely-designed dual-node Sun Blade X6275 server modules outfitted with most recent Intel Xeon processors and allow customers to quickly compare the performance of multiple available solutions while making their purchasing decisions.

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