Fluent World Records on Sun's Blades

Wednesday Jan 23, 2008

Two benchmark test suites (standard and new) for the Fluent computational fluid dynamics (CFD) code were run on a mini cluster of Sun Blade X6250 blades with the recently announced 3.33 GHz dual core Intel 5260. The Sun Blade X6250 mini cluster beats all posted results for both FLUENT benchmark test suites at each core level from one up to the maximum sixteen cores that were available on the X6250 cluster.

• In runs of the standard test suite the X6250 cluster was from 15% (lower core levels) to 42% (highest core level) faster than the previous top set of results posted from a Harpertown quad-core 3.0 GHz Xeon.
• The scaling efficiency with the X6250 cluster ranged from 100% to on average 84% going from 1 to 8 cores when running the standard large test cases.
• In runs of the new larger and more representative test suite, the X6250 cluster was from 15% (lower core levels) to 65% (highest core level) faster than the top results posted from a Harpertown quad-core 3.0 GHz Xeon.
• The scaling efficiency with the X6250 cluster ranged from 100% to on average 84% going from 1 to 8 cores when running all six of the test cases in the new test suite.

Four, 2-socket Sun X6250 blades with Infiniband interconnects were used. Comparisons are presented against the results posted at the FLUENT Performance website.

The two benchmark test suites that were considered are first, the long standing standard "FLUENT 6" benchmark test suite consisting of 9 test cases: 3 small, 3 medium sized, and 3 large and is referenced above as the standard test suite. Secondly, the "FLUENT 6.3" benchmark test suite (referenced as the new test suite) consisting of larger models (both in memory requirements and mesh/model size) more suited for multi core multi node dmp cluster run environments and more representative of current actual engineering CFD.

Fluent is one of the most prominent commercial CFD (Computational Fluid Dynamics) codes. It is distributed worldwide to major engineering organizations in a broad spectrum of disciplines (aircraft, aerospace, automotive, marine, etc.) that are involved with fluid flow.

CFD models tend to be extremely large (fluid flow over entire car, aircraft and submarine bodies and complex flow involving mixing of species and chemical reaction). In order to have reasonable run times for the analyses use of many processing units is necessary. Currently the most effective way of achieving this is via an interconnected cluster of multi-core rack-mounted servers or blades.

Standard FLUENT 6 Benchmark Test Suite, large workload results ("ratings" bigger is better)

Click www.fluent.com/software/fluent/fl6bench/fl6bench_6.3/ to see the full table of results.

Rating = No. of sequential runs of test case possible in 1 day 86,400/(Total Elapsed Run Time in Seconds)

System	NCPUS	FL5L1	FL5L2	FL5L3
Sun X6250 3.33GHz DC 5260	1	259.4	178.5	32.4
Intel 3.0GHz QC Harpertown	1	220.5	151.2	27.9
SGI Altix XE210 3.0GHz Xeon 5160	1	210.7	153.5	29.6
IBM X3550 3GHz DC 5160	1	188.0	134.7	n/a
Sun X6250 3.33GHz DC 5260	2	493.4	351.8	61.9
Intel 3.0GHz QC Harpertown	2	420.7	297.3	54.2
SGI Altix XE210 3.0GHz Xeon 5160	2	396.1	298.0	56.2
IBM X3550 3GHz DC 5160	2	342.6	236.8	55.0
Sun X6250 3.33GHz DC 5260	4	931.8	675.7	122.0
SGI Altix XE210 3.0GHz Xeon 5160	4	679.2	449.7	80.7
IBM X3550 3GHz DC 5160	4	623.5	411.4	94.9
Sun X6250 3.33GHz DC 5260	8	1811.3	1227.3	207.2
Intel 3.0GHz QC Harpertown	8	1279.1	710.5	120.0
SGI Altix XE210 3.0GHz Xeon 5160	8	1343.7	899.5	161.0
IBM X3550 3GHz DC 5160	8	1273.4	862.3	149.9
Sun X6250 3.33GHz DC 5260	16	2941.3	1577.4	246.0
SGI Altix XE210 3.0GHz Xeon 5160	16	2584.9	1788.8	319.0
IBM X3550 3GHz DC 5160	16	2479.2	1722.0	306.8

New FLUENT 6.3 Benchmark Test Suite, "Ratings" (bigger is better)

Rating = No. of sequential runs of test case possible in 1 day 86,400/(Total Elapsed Run Time in Seconds)

System	NCPUS	eddy	turbo	aircraft	sedan	truck14m	truckpoly
Sun X6250 3.33GHz DC 5260	1	109.2	440.4	96.6	65.1	7.0	8.3
Intel 3.0GHz QC Harpertown	1	95.9	n/a	84.2	55.9	6.2	6.9
Sun X6250 3.33GHz DC 5260	2	208.9	823.1	178.8	121.3	14.6	16.1
Intel 3.0GHz QC Harpertown	2	183.1	741.3	162.9	109.6	12.4	13.4
Sun X6250 3.33GHz DC 5260	4	415.6	1590.4	353.8	246.2	29.9	31.9
Sun X6250 3.33GHz DC 5260	8	780.8	2805.2	577.1	384.4	55.0	57.3
Intel 3.0GHz QC Harpertown	8	491.4	1685.0	321.0	207.2	32.1	33.2
Sun X6250 3.33GHz DC 5260	16	1095.8	3744.3	682.9	429.9	73.7	74.6

Key Technical Points

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Posted at 06:01AM Jan 23, 2008 by BM Seer in Benchmarks
Tags: blade fluent performance

CFD World Record Fluent Sun Blade X6250 Cluster (Xeon 3 GHz 5160)

Thursday Jul 12, 2007

The Sun Blade X6250 cluster was up to 27% faster or 6% faster on geometric mean than an SGI Altix XE 210 cluster (Xeon 3 GHz dual core 5160 Woodcrest) and Infiniband interconnects.

A cluster of four Sun Blade X6250 Cluster (Xeon 3 GHz 5160) with Infiniband interconnects was used to set this record. Each of these two socket blades had dual-core Intel Xeon EM64T 5160 3 GHz (Woodcrest) 16 total cores.

The Sun Blade X6250 Cluster (Xeon 3 GHz 5160) cluster running computational fluid dynamics program (CFD) the "Fluent 6" standard benchmark established a world record for runs made of the test suite using from 1 to 16 cores.

Workload description

Fluent is one of the most prominent commercial CFD (Computational Fluid Dynamics) codes. It is distributed worldwide to major engineering organizations in a broad spectrum of disciplines (aircraft, aerospace, automotive, marine, etc.) that are involved with fluid flow in some manner.

Fluent like many major ISV's has developed a benchmark test suite to evaluate the performance of platforms. For several years results have been posted from hardware vendor platforms at the Fluent website.

CFD models tend to be extremely large (fluid flow over entire car, aircraft and submarine bodies and complex flow involving mixing of species and chemical reaction). In order to have reasonable run times for the analyses use of many processing units is necessary. Currently the most effective way of achieving this is via an interconnected cluster of multi core rack mounted servers or blades. The current set of entries posted at the Fluent website reflect this fact.

FLUENT 6 Benchmark ("Ratings", bigger is better)

Rating = #f sequential runs in 1 day 86,400/(Total Elapsed Run Time in Seconds)

Machine	Sockets	NCPUS	FL5M1	FL5M2	FL5M3	FL5L1	FL5L2	FL5L3
Sun Blade X6250 3GHz WC 5160	2	8	4965.5	10504.6	2563.8	1399.2	1028.3	174.9
SGI Altix XE210 3GHz WC 5160	2	8	4937.1	9626.7	2014.0	1343.7	899.5	161.0
Sun Blade X6250 3GHz WC 5160	2	4	2780.4	5358.1	1336.9	731.7	573.7	101.2
SGI Altix XE210 3GHz WC 5160	2	4	2681.1	4657.7	998.0	679.2	449.7	80.7
Sun Blade X6250 3GHz WC 5160	2	serial	919.4	1465.6	352.9	207.2	142.6	27.6
SGI Altix XE210 3GHz 5160	2	serial	910.9	1445.4	349.5	204.1	136.6	26.8

Other interesting points:

• The "Fluent 6" standard benchmark test suite consists of "small" "medium" and "large " test cases. However both the small and medium sized test cases are all really on the small side and do not scale well beyond 16 cores.
• The largest test case in the suite, "fl5l3" requires 9 GB running with only one core on a single node. This memory requirment per node is reduced when running in a dmp cluster mode on multi nodes with multi cores.
• Fluent runs are cpu and sometimes memory intensive but do not require high performance I/O file systems.
• Very recently Fluent has devloped a new benchmark test suite with extremely large models specifically intended to be run either on large multi core servers or large multi node clusters of multi core platforms.

Workload Details

Nine industrial CFD applications ranging in size from 32,000 to 10,000,000 cells have been selected to demonstrate the performance of FLUENT on a variety of hardware platforms. The performance of a CFD code will depend on several factors including size and topology of the mesh, physical models, etc. The test cases represent a range of typical industry simulations.

Descriptions
Class   Benchmark       Cells   Mesh    Models  Solver  Description
small   
        FL5S1          32,000 hexahedral ke  segregated implicit  turbulent flow in a bend
        FL5S2          32,000 hexahedral ke  coupled implicit     turbulent flow in a bend
        FL5S3          89,856 hexahedral ke  coupled implicit     flow in a compressor, rotor 37
medium  
        FL5M1         155,188 tetrahedral ke  6spe reac DPM P1 segregated implicit coal combustion in a boiler, with particle tracking
        FL5M2         242,782 hybrid, hanging-node ke segregated implicit turbulent flow in an engine valveport
        FL5M3         352,800 hexahedral ke 6spe react segregated implicit combustion in a high velocity burner
large   
        FL5L1         847,746 hexahedral ke coupled explicit transonic flow around a fighter
        FL5L2       3,618,080  hybrid  RNG ke segregated implicit external aerodynamics around a car body
        FL5L3       9,792,512  hexahedral RSM segregated implicit turbulent flow in a transition duct

Small Class Ratings

Small class problems contain less than 100,000 cells.

FL5S1 - Accelerating turbulent flow in an elbow duct using segregated implicit solver
Accelerating Turbulent Flow in an Elbow Duct using Segregated Implicit Solver

Flow is accelerated through a 90 degree elbow duct with a rectangular
cross section. The geometry and flow have a symmetry plane permitting
the modeling of only half the domain. Because of the curvature of the
duct, significant secondary flow occurs, with velocity components
normal to the principal flow direction. The segregated implicit solver
in FLUENT 5 is used to solve this flow.

Number of cells 32,000
Cell type hexahedral
Models k-epsilon turbulence
Solver segregated implicit

FL5S2 - Accelerating turbulent flow in an elbow duct using coupled implicit solver
Accelerating Turbulent Flow in an Elbow Duct using Coupled Implicit Solver

Flow is accelerated through a 90 degree elbow duct with a rectangular
cross section. The geometry and flow have a symmetry plane permitting
the modeling of only half the domain. Because of the curvature of the
duct, significant secondary flow occurs, with velocity components
normal to the principal flow direction. The coupled implicit solver in
FLUENT 5 is used to solve this flow.

Number of cells 32,000
Cell type hexahedral
Models k-epsilon turbulence
Solver coupled implicit

FL5S3 - Transonic flow in rotating fan
Transonic Flow through a Rotor

The flow through a transonic fan rotor (designated rotor 37 by NASA
Lewis) was computed. It has 36 blades. The calculation was performed at
a rotational speed of 17189 rpm. The domain boundaries consist of a
hub, blade and shroud surface, a pressure inlet and outlet surface, and
periodic surfaces.

Number of cells 89,856
Cell type hexahedral
Models k-epsilon turbulence
Solver coupled implicit


Medium class problems contain between 100,000 and 500,000 cells.

FL5M1 - Coal combustion in a boiler
Coal Combustion in a Boiler

This application couples a continuous gas phase calculation with a
discrete phase (particle) calculation. 500 coal particles are injected
into an industrial boiler where their trajectories are computed using a
Lagrangian formulation that includes dispersed phase inertia,
hydrodynamic drag and the force of gravity. Each particle injection is
subject to heating/cooling, vaporization, boiling and solid combustion.
During the injection calculations, momentum, heat and mass exchanges
are calculated and stored as source terms which are then used in the
subsequent gas phase calculation. Furthermore, stochastic modeling of
particle tracks, requiring a fixed number of "tries" per particle, are
used to account for local turbulent fluctuations. In this calculation,
10 stochastic tries per particle are used, resulting in a total of 5000
particle tracks per discrete phase update. There are 10 continuous
phase iterations per discrete phase update.

Number of cells 155,188
Cell type tetrahedral
Models k-epsilon turbulenc 6 species with reaction dispersed phase
P1 radiation
Solver segregated implicit

FL5M2 - Turbulent flow in an engine valveport
Turbulent Flow in an Engine Valveport

Flow is computed in an automotive valve port modeled using a zonal
hybrid mesh. The region around the valve has been meshed with
tetrahedral cells, while the duct providing the inlet flow to the valve
has been meshed with hexahedra. Pyramid cells are used to transition
between the hexahedral and tetrahedral cells. A fourth cell type called
a prismatic (or wedge) cell is used for the cylinder downstream of the
valve. Furthermore, hanging-node adaption was used to improve the
accuracy of the predicted flow field.

Number of cells 242,782
Cell type hybrid hanging-node adaption
Models k-epsilon turbulence
Solver segregated implicit

FL5M3 - Combustion in a high velocity burner
Combustion in a High Velocity Burner

Fuel (CH4) is injected into ports of a high velocity gas burner located
near the centerline. Air is supplied through the outer ports, with
secondary air delivered into an outer annular region. Directly
downstream of the annulus is a wedge-shaped annular baffle. The mixing
of fuel and air occurs downstream of this baffle and recirculation
zones behind the baffle provide stability and an attachment point for
the flame in the main combustion chamber. Combustion is assumed to
proceed via a two-step reaction mechanism, with turbulent mixing as the
limiting rate, as described by the Magnessen model.

Reference: M. Cavelli, A. Milani, "Spark-ignited wide stability gas
burner for on/off and continuous duty," IFRF HT Meeting, Milan, October
1996.

Number of cells 352,800
Cell type hexahedral
Models k-epsilon turbulenc 6 species with reaction
Solver segregated implicit

Large Class

Large class problems contain more than 500,000 cells.

FL5L1 Transonic flow around a fighter aircraft
Transonic Flow Around a Fighter Aircraft

Flow around the AGARD M-151 combat aircraft research model is computed.
The simulation geometry contains canards and forward swept wings, but
no tail. The conditions modeled were Mach number 0.9 and 10.46 degrees
angle of attack.

Number of cells 847,764
Cell type hexahedral
Models k-epsilon turbulence
Solver segregated implicit

FL5L2 Exterior flow around a passenger sedan
Exterior Flow Around a Passenger Sedan

This benchmark represents the computation of the exterior flow field
around a simplified model of a passenger sedan. The simulation geometry
was used for the Japan External Aerodynamics competition. A
viscous-hybrid grid with prismatic cells is used to adequately model
the boundary layer regions.

Number of cells 3,618,080
Cell type

FL5L2 Exterior flow around a passenger sedan
Exterior Flow Around a Passenger Sedan

This benchmark represents the computation of the exterior flow field
around a simplified model of a passenger sedan. The simulation geometry
was used for the Japan External Aerodynamics competition. A
viscous-hybrid grid with prismatic cells is used to adequately model
the boundary layer regions.

Number of cells 3,618,080
Cell type hybrid
Models k-epsilon turbulence
Solver segregated implicit

FL5L3 Turbulent flow through a transition duct
Turbulent Flow Through a Transition Duct

Turbulent flow of air through a duct is computed for this benchmark.
The cross-sectional planes of the duct transition from a circle at the
inlet to a rectangle at the outflow boundary. The Reynolds-Stress Model
(7 equation) is used for computing turbulence.

Number of cells 9,792,512
Cell type hexahedral
Models RSM turbulence
Solver segregated implicit

The cluster of Sun Blade X6250 outperfomed the following competitive hardware vendor clusters at all core levels considered (1 core smp, 1- core parallel, 2- 4- 8- and 16-core parallel runs) and for all (9) test cases in the benchmark test suite:

HP BL460C (EM64T_WOODCREST_2CORE,3000,WINCCS,IB_HPMPI)
HP DL140 (EM64T_WOODCREST_2CORE,3000,LINUX,IB)
HP DL145_G2 (OPTERON_2CORE,2200,WINCCS,IB_HPMPI)
SGI ALTIX4700 (IA64_MONTECITO_2CORE,1600,LINUX)
SGI ALTIXXE210 (EM64T_WOODCREST_2CORE,3000,LINUX,IB_VOLTAIRE)
TYAN TYPHOON_630 (EM64T_WOODCREST_2CORE,2300,SLES10,GIGE)
TYAN TYPHOON_630 (EM64T_WOODCREST_2CORE,2300,WINCCS,GIGE)
BULL NOVASCALE (EM64T_WOODCREST_2CORE,3000,RHEL4,IB)
APPRO XTREMESERVER (OPTERON_2CORE,2800,RHEL4,IB)

Disclosure Statement:

All information on the Fluent website is Copyrighted 1995-2007 by Fluent Inc.Results from http://www.fluent.com/software/fluent/fl5bench/flbench_6.3/fullres.htm as of July 2, 2007.

Sun Blade X6250

4 2-socket Sun Blade X6250's
2x3.0 GHz DC Intel Xeon EM64T 5160 (Woodcrest)
Infiniband (Voltaire) Interconnects (PCI-Express HCA's)

Software Configuration:

64-bit SUSE SLES 10
Fluent V6.3.26
Fluent 6 Standard Benchmark Test Suite
Voltaire GridStack 4.1.5-7 for SLES 10

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Posted at 06:15PM Jul 12, 2007 by BM Seer in Benchmarks
Tags: cfd fluent hpc performance x6250

Sun Fire X2200 M2 running Fluent CFD Beats Woodcrest & Clovertown

Friday Mar 30, 2007

The Sun Fire X2200 M2 server beats Woodcrest on large CFD models. The X2200 M2 Cluster beats all currently posted Opteron cluster results (dual core HP XC4000 2.2GHz, HP DL145 G2 2.2GHz, HP XW9300 2.4GHz, and HP DL585 2.6GHz) for all "cpu" levels and for all test cases. All clusters had the high performance Infiniband interconnects.

The X2200 M2 beats the IBM X3650 2.66GHz quad core Clovertown across the board at all cpu levels and for all test cases.

Tests were run on the official version of Fluent (lnxamd64 V6.3.26 build). The Sun Opteron server numbers were generated under 64-bit SUSE SLES 9 SP 3. Sun many customers that use Solaris, Linux, and windows so we show benchmarks on all of these.

Although the X2200 M2 cluster has the best performance on the larger and more complex tests, "FL5L3". It is most closely representative of actual customer benchmarks (requires over 9GB of memory, best run using several cpu's). FL5L3 simulates turbulent flow through a transition duct.

Note that the X2200 M2 cluster results shown in following table are consistently better than those obtained on the two Woodcrest cluster systems at the same "cpu" levels and for all indicated "cpu" levels (4 to 32).

The efficiency of the Sun X2200 M2 cluster is superb at well above 90% up to 32 cores. This essentially perfect scalability is contrasted with the Woodcrest clusters where scalability has dropped off and efficiency is below 70% at and above 4 cores.

Scaling Performance : Results in "Ratings" (# runs/day, bigger is better)

System	4 Cores	8 Cores	16 Cores	32 Cores
Sun X2200 M2 2.8GHz Operton	89.9	174.4	341.5	664.4
HP BL460C 3.0GHz Woodcrest	80.3	155.4	299.0	576.0
HP DL140 3.0GHz Woodcrest	N/A	160.7	320.5	620.1
Bull NovaScale 3.0GHz Woodcrest	78.9	157.8	313.2	619.0

Fluent Performance : Results in "Ratings" (# runs/day, bigger is better)

System	Interconnect/MPI	cores	FL5L1	FL5L2	FL5L3
X2200 2.8GHz DC 2220 SLES 9 SP 3	IB(V)/HP-MPI	8	1219.5	952.1	174.4
X2100 3.0GHz SC 156 SLES 9 SP3	IB(V)/MVAPICH	8	1148.2	1063.4	184.6
HPDL140 3.0GHz DC WC EM64T Linux	IB/HP-MPI	8	1378.0	915.0	160.7
Bull Nova 3.0 GHz DC WC EM64T RHEL4	IB	8	1323.6	884.1	157.8
HP BL460C 3.0GHz WC EM64T WinCCS	IB(V)	8	1289.6	881.6	155.4
Intel White 3.0GHz WC EM64T DC RHAS4	IB(Mellanox)	8	---	828.0	137.8
Tyan Typh. 630 2.3GHz WC SLES 10	GbE	8	1011.7	692.4	122.7
Tyan Typh. 630 2.3GHz WC WinCCS	GbE	8	981.8	635.3	---
HPDL140 3.6GHz EM64T WINCCS	IB	8	970.8	675.0	120.0
HPDL585 2.6GHz DC 152 RHEL4	IB(V)/HP-MPI	8	966.2	723.2	119.2
HPXC4000 2.2GHz DC 148 Linux	IB(V)/HP-MPI	8	951.0	680.4	102.7
HPDL145 G2 Opteron 2.2GHz DC WinCCS	IB(V)	8	847.1	654.5	119.2
IBMX3650 2.66GHz 4C Clovert. EM64T RHEL4	?	8	953.6	551.2	93.3

Benchmark Description

Nine industrial CFD applications ranging in size from 32,000 to 10,000,000 cells have been selected to demonstrate the performance of FLUENT on a variety of hardware platforms. The performance of a CFD code will depend on several factors including size and topology of the mesh, physical models, numerics and parallelization, compilers and optimization, in addition to performance characteristics of the hardware where the simulation is performed. The problems selected represent a range of simulations typical of those which might be found in industry. The principal objective of this benchmark suite is to provide comprehensive and fair comparative information of the performance of FLUENT on available hardware platforms.

System Configuration

Hardware Configuration:

Sun Fire X2200 M2
2-socket 2x2.8 GHz dual core Opteron 2220 processors
4x1GB + 4x2GB (12GB) DDR2 667 MHz dimms
IB(Voltaire)/PCI-Express (interconnect)

Software Configuration:

64-bit SuSE SLES 9 SP 3
Fluent V6.3.26
Voltaire Infiniband Software Stack: 3.5.5_16-S2sles9.k2.6.5_7.244_smp.x86_64
Message Passing Interface: HP-MPI V hpmpi-2.02.05.00-20061003r.x86_64

See Also

Current V6.2(.16) results at:
http://www.fluent.com/software/fluent/fl5bench/flbench_6.3/fullres.htm

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Posted at 11:04AM Mar 30, 2007 by BM Seer in Benchmarks
Tags: cfd clovertown fire fluent m2 opteron sun woodcrest x2200

Sun Opteron x4100 outscaling woodcrest part 2

Wednesday Nov 15, 2006

As mentioned in the posting earlier today, scalability is important factor in system performance. Woodcrest's poor scaling may not bode well for Cloverton. Sure you can package for threads onto a module, but unless you design for them you'll just have more threads not delivering performance but just burning more watts.

Wattage: I'll get detailed wattage results posted soon, but it looks like as we mentioned Opteron performance is about 20% more than Woodcrest. The wattage for both configurations looks the same. Therefore expect Sun's Opteron to have about 20% perf/watt advantage.

Sun's Fluent results will be posted shortly on the website, it is a busy week with Supercomputing conference and lots of busy people. So keep checking back. A few of the smaller gave Woodcrest a small percent advantage, but most were significantly faster on Sun's Opteron.

...maybe Woodcrest will have better idle power, but why in the world would you buy the latest server and leave it idle?

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Posted at 02:59PM Nov 15, 2006 by BM Seer in Benchmarks
Tags: fluent opteron x4100

Sun Opteron x4100 outscaling woodcrest (and outperforming = side benefit)

Wednesday Nov 15, 2006

Woodcrest scaling issues? Yes, remember scaling is critical for system performance, so don't look too much at single core performance or single job performance as it can lead to the wrong conclusions. In fact Sun's Opteron scaling means that the Sun systems can outperform Woodcrest by 18% to 22% as shown below.

On a 4 core/2chip Intel Woodcrest systems they are only seeing 2.8x to 2.9x on 4 cores -- this doesn't bode well for quad-core or larger systems made out of these. Sun sees 3.6x to 4.1x scaling in the table below. Couple this with the high-wattage of these Woodcrest (31-Oct posting) and Woodcrest may have issues?

Opteron leads poor Woodcrest scaling & performance on Fluent 6 Benchmark (Both systems 2 sockets and using dual-core)

System	GHz/Chip	#cores	FL5M3 (scaling)	FL5L2 (scaling)
INTEL S5000XAL	3.0GHz Xeon Woodcrest 5160	4-core	827.0 (2.8x)	400.0 (2.9x)
INTEL S5000XAL	3.0GHz Xeon Woodcrest 5160	2-core	553.7 (1.9x)	226.0 (1.6x)
INTEL S5000XAL	3.0GHz Xeon Woodcrest 5160	1-core	297.3 (1.0x)	138.0 (1.0x)
Sun
Sun X4100 M2	2.8GHz Opteron DC 2200	4-core	979.9 (3.6x)	486.6 (4.1x)
Sun X4100 M2	2.8GHz Opteron DC 2200	2-core	516.1 (1.9x)	241.8 (2.1x)
Sun X4100 M2	2.8GHz Opteron DC 2200	1-core	273.5 (1.0x)	117.6 (1.0x)

Rating = No. of sequential runs of test case possible in 1 day, 86,400/(Total Elapsed Run Time in Seconds)

Fluent results at: http://www.fluent.com/software/fluent/fl5bench/flbench_6.2/fullres.htm

...I suspect even better performance and scaling on Sun Fire X4100 M2 with Solaris...

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Posted at 07:28AM Nov 15, 2006 by BM Seer in Benchmarks
Tags: fluent opteron scaling sun woodcrest

Woodcrest scaling problems? (Fluent part1)

Friday Nov 03, 2006

Does the Woodcrest have scaling issues now? It may be caused by the rush to increase core count without really considering design. On a 4 core/2chip Intel Woodcrest systems we are only seeing 3.0x to 3.3x on 4 cores -- this doesn't bode well for quad-core or larger systems made out of these. Couple this with the high-wattage of these chips (Tuesday's posting) and this chip may have issues?

Poor Woodcrest scaling & Performance on Fluent 6 Benchmark

System	GHz/Chip	#cores	FL5L1 (scaling)	FL5L2 (scaling)
INTEL S5000XAL	3.0GHz Xeon Woodcrest 5160	4-core 2-Socket	631.8 (3.3x)	400.0 (3.0x)
INTEL S5000XAL	3.0GHz Xeon Woodcrest 5160	2-core 1-Socket	372.8 (1.9x)	226.0 (1.7x)
INTEL S5000XAL	3.0GHz Xeon Woodcrest 5160	1-core	194.0 (1.0x)	133.0 (1.0x)

Rating = No. of sequential runs of test case possible in 1 day, 86,400/(Total Elapsed Run Time in Seconds)

Fluent results at: http://www.fluent.com/software/fluent/fl5bench/flbench_6.2/fullres.htm

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Posted at 04:45PM Nov 03, 2006 by BM Seer in Intel follies
Tags: fluent issues scaling woodcrest