BestPerf: Performance & Best Practices

Part of the Sun FlashFire family, the Sun Flash Accelerator F20 PCIe Card is a low-profile x8 PCIe card with 4 Solid State Disks-on-Modules (DOMs) delivering over 101K IOPS (4K IO) and 1.1 GB/sec throughput (1M reads).

The Sun F20 card is designed to accelerate IO-intensive applications, such as databases, at a fraction of the power, space, and cost of traditional hard disk drives. It is based on enterprise-class SLC flash technology, with advanced wear-leveling, integrated backup protection, solid state robustness, and 3M hours MTBF reliability.

• The Sun Flash Accelerator F20 PCIe Card demonstrates breakthrough performance of 101K IOPS for 4K random read
• The Sun Flash Accelerator F20 PCIe Card can also perform 88K IOPS for 4K random write
• The Sun Flash Accelerator F20 PCIe Card has unprecedented throughput of 1.1 GB/sec.

• The Sun Flash Accelerator F20 PCIe Card (low-profile x8 size) has the IOPS performance of over 550 SAS drives or 1,100 SATA drives.

Performance Landscape

Bandwidth and IOPS Measurements

Test	DOMs
	4	2	1
Random 4K Read	101K IOPS	68K IOPS	35K IOPS
Maximum Delivered Random 4K Write	88K IOPS	44K IOPS	22K IOPS
Maximum Delivered 50-50 4K Read/Write	54K IOPS	27K IOPS	13K IOPS
Sequential Read (1M)	1.1 GB/sec	547 MB/sec	273 MB/sec
Maximum Delivered Sequential Write (1M)	567 MB/sec	243 MB/sec	125 MB/sec
Sustained Random 4K Write*	37K IOPS	18K IOPS	10K IOPS
Sustained 50/50 4K Read/Write*	34K IOPS	17K IOPS	8.6K IOPS

(*) Maximum Delivered values measured over a 1 minute period. Sustained write performance differs from maximum delivered performance. Over time, wear-leveling and erase operations are required and impact write performance levels.

Latency Measurements

The Sun Flash Accelerator F20 PCIe Card is tuned for 4 KB or larger IO sizes, the write service for IOs smaller than 4 KB can be 10 times more than shown in the table below. It should also be noted that the service times shown below are both the latency and the time to transfer the data. This becomes the dominant portion the the service time for IOs over 64 KB in size.

Transfer Size	Service Time (ms)
	Read	Write
4 KB	0.32	0.22
8 KB	0.34	0.24
16 KB	0.37	0.27
32 KB	0.43	0.33
64 KB	0.54	0.46
128 KB	0.49	1.30
256 KB	1.31	2.15
512 KB	2.25	2.25

- Latencies are measured application latencies via vdbench tool.
- Please note that the FlashFire F20 card is a 4KB sector device. Doing IOs of less than 4KB in size, or not aligned on 4KB boundaries, can result in a significant performance degradations on write operations.

Results and Configuration Summary

Storage:

Sun Flash Accelerator F20 PCIe Card
4 x 24-GB Solid State Disks-on-Modules (DOMs)

Servers:

1 x Sun Fire X4170

Software:

OpenSolaris 2009.06 or Solaris 10 10/09 (MPT driver enhancements)
Vdbench 5.0
Required Flash Array Patches SPARC, ses/sgen patch 138128-01 or later & mpt patch 141736-05
Required Flash Array Patches x86, ses/sgen patch 138129-01 or later & mpt patch 141737-05

Benchmark Description

Sun measured a wide variety of IO performance metrics on the Sun Flash Accelerator F20 PCIe Card using Vdbench 5.0 measuring 100% Random Read, 100% Random Write, 100% Sequential Read, 100% Sequential Write, and 50-50 read/write. This demonstrates the maximum performance and throughput of the storage system.

Vdbench profile f20-parmfile.txt is here for bandwidth and IOPs. And here is the vdbench profile f20-latency.txt file for latency.

Vdbench is publicly available for download at: http://vdbench.org

Key Points and Best Practices

• Drive each Flash Modules with 32 outstanding IO as shown in the benchmark profile above.
• SPARC platforms will align with the 4K boundary size set by the Flash Array. x86/windows platforms don't necessarily have this alignment built in and can show lower performance

See Also

• Vdbench is publicly available for download at: http://vdbench.org
• Information on how to do alignments at http://wikis.sun.com/display/Performance/Home#Home-Flash

Disclosure Statement

Sun Flash Accelerator F20 PCIe Card delivered 100K 4K read IOPS and 1.1 GB/sec sequential read. Vdbench 5.0 (http://vdbench.org) was used for the test. Results as of September 14, 2009.

TPC-C Sun SPARC Enterprise T5440 with Oracle RAC World Record Database Result

Sun and Oracle demonstrate the World's fastest database performance. Sun Microsystems using 12 Sun SPARC Enterprise T5440 servers, 60 Sun Storage F5100 Flash arrays and Oracle 11g Enterprise Edition with Real Application Clusters and Partitioning delivered a world-record TPC-C benchmark result.

• The 12-node Sun SPARC Enterprise T5440 server cluster result delivered a world record TPC-C benchmark result of 7,646,486.7 tpmC and $2.36 $/tpmC (USD) using Oracle 11g R1 on a configuration available 12/14/09.

• The 12-node Sun SPARC Enterprise T5440 server cluster beats the performance of the IBM Power 595 (5GHz) with IBM DB2 9.5 database by 26% and has 16% better price/performance on the TPC-C benchmark.
  

• The complete Oracle/Sun solution used 10.7x better computational density than the IBM configuration (computational density = performance/rack).

• The complete Oracle/Sun solution used 8 times fewer racks than the IBM configuration.

• The complete Oracle/Sun solution has 5.9x better power/performance than the IBM configuration.

• The 12-node Sun SPARC Enterprise T5440 server cluster beats the performance of the HP Superdome (1.6GHz Itanium2) by 87% and has 19% better price/performance on the TPC-C benchmark.

• The Oracle/Sun solution utilized Sun FlashFire technology to deliver this result. The Sun Storage F5100 flash array was used for database storage.

• Oracle 11g Enterprise Edition with Real Application Clusters and Partitioning scales and effectively uses all of the nodes in this configuration to produce the world record performance.

• This result showed Sun and Oracle's integrated hardware and software stacks provide industry-leading performance.

More information on this benchmark will be posted in the next several days.

Performance Landscape

TPC-C results (sorted by tpmC, bigger is better)

System	tpmC	Price/tpmC	Avail	Database	Cluster	Racks	w/KtpmC
12 x Sun SPARC Enterprise T5440	7,646,487	2.36 USD	12/14/09	Oracle 11g RAC	Y	9	9.6
IBM Power 595	6,085,166	2.81 USD	12/10/08	IBM DB2 9.5	N	76	56.4
HP Integrity Superdome	4,092,799	2.93 USD	08/06/07	Oracle 10g R2	N	46	to be added

Avail - Availability date
w/KtmpC - Watts per 1000 tpmC
Racks - clients, servers, storage, infrastructure

Sun and IBM TPC-C Response times

System	tpmC	Response Time New Order 90th%	Response Time New Order Average
12 x Sun SPARC Enterprise T5440	7,646,487	0.170	0.168
IBM Power 595	6,085,166	1.69	1.22
Response Time Ratio - Sun Better		9.9x	7.3x

Sun uses 7x comparison to highlight the differences in response times between Sun's solution and IBM.  Although notice that Sun is 10x faster on New Order transactions that finish in the 90% percentile.

It is also interesting to note that none of Sun's response times, avg or 90th percentile, for any transaction is over 0.25 seconds. While IBM does not have even one interactive transaction, not even the menu, below 0.50 seconds. Graphs of Sun's and IBM's response times for New-Order can be found in the full disclosure reports on TPC's website TPC-C Official Result Page.

Results and Configuration Summary

Hardware Configuration:

9 racks used to hold

Servers:

12 x Sun SPARC Enterprise T5440
4 x 1.6 GHz UltraSPARC T2 Plus
512 GB memory
10 GbE network for cluster

Storage:

60 x Sun Storage F5100 Flash Array
61 x Sun Fire X4275, Comstar SAS target emulation
24 x Sun StorageTek 6140 (16 x 300 GB SAS 15K RPM)
6 x Sun Storage J4400
3 x 80-port Brocade FC switches

Clients:

24 x Sun Fire X4170, each with
2 x 2.53 GHz X5540
48 GB memory

Software Configuration:

Solaris 10 10/09
OpenSolaris 6/09 (COMSTAR) for Sun Fire X4275
Oracle 11g Enterprise Edition with Real Application Clusters and Partitioning
Tuxedo CFS-R Tier 1
Sun Web Server 7.0 Update 5

Benchmark Description

TPC-C is an OLTP system benchmark. It simulates a complete environment where a population of terminal operators executes transactions against a database. The benchmark is centered around the principal activities (transactions) of an order-entry environment. These transactions include entering and delivering orders, recording payments, checking the status of orders, and monitoring the level of stock at the warehouses.

See Also

• TPC-C Official Result Page
  

• www.tpc.org Website

Disclosure Statement

TPC Benchmark C, tpmC, and TPC-C are trademarks of the Transaction Performance Processing Council (TPC). 12-node Sun SPARC Enterprise T5440 Cluster (1.6GHz UltraSPARC T2 Plus, 4 processor) with Oracle 11g Enterprise Edition with Real Application Clusters and Partitioning, 7,646,486.7 tpmC, $2.36/tpmC. Available 12/14/09. IBM Power 595 (5GHz Power6, 32 chips, 64 cores, 128 threads) with IBM DB2 9.5, 6,085,166 tpmC, $2.81/tpmC, available 12/10/08. HP Integrity Superdome(1.6GHz Itanium2, 64 processors, 128 cores, 256 threads) with Oracle 10g Enterprise Edition, 4,092,799 tpmC, $2.93/tpmC. Available 8/06/07. Source: www.tpc.org, results as of 11/5/09.

Overview and Significance of Results

Oracle and Sun's Flash Cache technology combines New features in Oracle with the Sun Storage F5100 to improve database performance. In Oracle databases, the System Global Area (SGA) is a group of shared memory areas that are dedicated to an Oracle “instance” (Oracle processes in execution sharing a database) . All Oracle processes use the SGA to hold information. The SGA is used to store incoming data (data and index buffers) and internal control information that is needed by the database. The size of the SGA is limited by the size of the available physical memory.

This benchmark tested and measured the performance of a new Oracle Database 11g (Release2) feature, which allows to extend the SGA size and caching beyond physical memory, to a large flash memory storage device as the Sun Storage F5100 flash array.

One particular benchmark test demonstrated a dramatic performance improvement (almost 5x) using the Oracle Extended SGA feature on flash storage by reaching SGA sizes in the hundreds of GB range, at a more reasonable cost than equivalently sized RAM and with much faster access times than disk I/O.

The workload consisted in a high volume of SQL select transactions accessing a very large table in a typical business oriented OLTP database. To obtain a baseline, throughput and response times were measured applying the workload against a traditional storage configuration and constrained by disk I/O demand (DB working set of about 3x the size of the data cache in the SGA). The workload was then executed with an added Sun Storage F5100 Flash Array configured to contain an Extended SGA of incremental size.

The tests have shown scaling throughput along with increasing Flash Cache size.

Table of Results

F5100 Extended SGA Size (GB)	Query Txns / Min	Avg Response Time (Secs)	Speedup Ratio
No	76338	0.118	N/A
25	169396	0.053	2.2
50	224318	0.037	2.9
75	300568	0.031	3.9
100	357086	0.025	4.6

Configuration Summary

Server Configuration:

Sun SPARC Enterprise M5000 Server
8 x SPARC64 VII 2.4GHz Quad Core
96 GB memory

Storage Configuration:

8 x Sun Storage J4200 Arrays, 12x 146 GB 15K RPM disks each (96 disks total)
1 x Sun Storage F5100 Flash Array

Software Configuration:

Oracle 11gR2
Solaris 10

Benchmark Description

The workload consisted in a high volume of SQL select transactions accessing a very large table in a typical business oriented OLTP database.

The database consisted of various tables: Products, Customers, Orders, Warehouse Inventory (Stock) data, etc. and the Stock table alone was 3x the size of the db cache size.

To obtain a baseline, throughput and response times were measured applying the workload against a traditional storage configuration and constrained by disk I/O demand. The workload was then executed with an added Sun Storage F5100 Flash Array configured to contain an Extended SGA of incremental size.

During all tests, the in memory SGA data cache was limited to 25 GB .

The Extended SGA was allocated on a “raw' Solaris Volume created with the Solaris Volume Manager (SVM) on a set of devices (Flash Modules) residing on the Sun Storage F5100 flash array.

Key Points and Best Practices

In order to verify the performance improvement brought by extended SGA, the feature had to be tested with a large enough database size and with a workload requiring significant disk I/O activity to access the data. For that purpose, the size of the database needed to be a multiple of the physical memory size, avoiding the case in which the accessed data could be entirely or almost entirely cached in physical memory.

The above represents a typical “use case” in which the Flash Cache Extension is able to show remarkable performance advantages.

If the DB dataset is already entirely cached, or the DB I/O demand is not significant or the application is already saturating the CPU for non database related processing, or large data caching is not productive (DSS type Queries), the Extended SGA may not improve performance.

It is also relevant to know that additional memory structures needed to manage the Extended SGA are allocated in the “in memory” SGA, therefore reducing its data caching capacity.

Increasing the Extended Cache beyond a specific threshold, dependent on various factors, may reduce the benefit of widening the Flash SGA and actually reduce the overall throughput.

This new cache is somewhat similar architecturally to the L2ARC on ZFS. Once written, flash cache buffers are read-only, and updates are only done into main memory SGA buffers. This feature is expected to primarily benefit read-only and read-mostly workloads.

A typical sizing of database flash cache is 2x to 10x the size of SGA memory buffers. Note that header information is stored in the SGA for each flash cache buffer (100 bytes per buffer in exclusive mode, 200 bytes per buffer in RAC mode), so the number of available SGA buffers is reduced as the flash cache size increases, and the SGA size should be increased accordingly.

Two new init.ora parameters have been introduced, illustrated below:

db_flash_cache_file = /lfdata/lffile_raw
db_flash_cache_size = 100G

The db_flash_cache_file parameter takes a single file name, which can be a file system file, a raw device, or an ASM volume. The db_flash_cache_size parameter specifies the size of the flash cache. Note that for raw devices, the partition being used should start at cylinder 1 rather than cylinder 0 (to avoid the disk's volume label).

See Also

• Lowering your IT costs with Oracle Database 11g Release 2

• Oracle Database 11g Release 2 new Features Guide

Disclosure Statement

Results as of October 10, 2009 from Sun Microsystems.

The Sun SPARC Enterprise T5440 server with 1.6GHz UltraSPARC T2 Plus with Solaris Containers, Sun Flash Open Storage, and Sun JAVA System Web Server 7.0 Update 5 achieved World Record SPECweb2005.

• Sun has obtained a World Record SPECweb2005 performance result of 100,209 SPECweb2005 on the Sun SPARC Enterprise T5440, running Solaris 10 10/09 Sun JAVA System Web Server 7.0 Update 5, and Java Hotspot™ Server VM.

• This result demonstrates performance leadership of the Sun SPARC Enterprise T5440 server and its scalability, by using Solaris Containers to consolidate multiple web serving environments, and Sun OpenStorage Flash technology to store large datasets for fast data retrieval.

• The Sun SPARC Enterprise T5440 delivers 21% greater SPECweb2005 performance than the HP DL370 G6 with 3.2GHz Xeon W5580 processors.

• The Sun SPARC Enterprise T5440 delivers 40% greater SPECweb2005 performance than the HP DL 585 G5 with four 3.114 GHz Opteron 8393 SE processors.

• The Sun SPARC Enterprise T5440 delivers 2x the SPECweb2005 performance of the HP DL 580 G5 with four 2.66GHz Xeon X7460 processors.

• There are no IBM Power6 results on the SPECweb2005 benchmark.

• This benchmark result clearly demonstrates that the Sun SPARC Enterprise T5440 running Solaris 10 10/09 and Sun Java System Webserver 7.0 Update 5 can support thousands of concurrent web server sessions and is an industry leader in web serving with a Sun solution.
  

Performance Landscape

Server	Processor	SPECweb2005	Banking*	Ecomm*	Support*	Webserver	OS
Sun T5440	4x 1.6 T2 Plus	100,209	176,500	133,000	95,000	Java WebServer	Solaris
HP DL370 G6	2x 3.2 W5580	83,073	117,120	142,080	76,352	Rock	RedHat Linux
HP DL585 G5	4x 3.11 O8393	71,629	117,504	123,072	56,320	Rock	RedHat Linux
HP DL580 G5	4x 2.66 X7460	50,013	97,632	69,600	40,800	Rock	RedHat Linux

* Banking - SPECweb2005-Banking
   Ecomm - SPECweb2005-Ecommerce
   Support - SPECweb2005-Support

Results and Configuration Summary

Hardware Configuration:

  1 Sun SPARC Enterprise T5440 with

• 4 x UltraSPARC T2 Processor 8 core, 64 threads, 1.6 GHz
• 254 GB memory
• 6 x 4Gb PCI Express 8-Port Host Adapter (SG-XPCIE8SAS-E-Z)
• 1 x Sun Storage F5100 Flash Array (TA5100RASA4-80AA)
• 1 x Sun Storage F5100 Flash Array (TA5100RASA4-40AA)

Server Software Configuration:

• Solaris 10 10/09
• JAVA System Web Server 7.0 Update 5
• Java Hotspot™ Server VM

Network configuration:

• 1 x Arista DCS-7124s 24-10GbE port  switch
• 1 x Cisco 2970 series (WS-C2970G-24TS-E) switch for the three 1 GbE networks

Back-end Simulator:

  1 Sun Fire X4270 with

• 2 x 2.93 GHz Intel X5570 Quad core
• 48GB memory
• Solaris 10 10/09
• JSWS 7.0 Update 5
• Java Hotspot™ Server VM

Clients:

  8 Sun Blade™ T6320

• 1 x 1.417 GHz UltraSPARC-T2
• 64 GB memory
• Solaris 10 5/09
• Java Hotspot™ Server VM

  8 Sun Blade™ 6270

• 2 x 2.93 GHz Intel X5570 Quad core
• 36 GB memory
• Solaris 10 5/09
• Java Hotspot™ Server VM

Benchmark Description

SPECweb2005, successor to SPECweb99 and SPECweb99_SSL, is an industry standard benchmark for evaluating Web Server performance developed by SPEC. The benchmark simulates multiple user sessions accessing a Web Server and generating static and dynamic HTTP requests. The major features of SPECweb2005 are:

• Measures simultaneous user sessions
• Dynamic content: currently PHP and JSP implementations
• Page images requested using 2 parallel HTTP connections
• Multiple, standardized workloads: Banking (HTTPS), E-commerce (HTTP and HTTPS), and Support (HTTP)
• Simulates browser caching effects
• File accesses more accurately simulate today's disk access patterns

Key Points and Best Practices

• The server was divided into four Solaris Containers and a single web server instance was executed in each container.
  
• Four processor sets were created (with varying numbers of threads depending on the workload) to run the web server in. This was done to reduce memory access latency using the physical memory closest to the processor.  All interrupts were run on the remaining threads.
  
• Each web server is executed in the FX scheduling class to improve performance by reducing the frequency of context switches.
• Two Sun Storage F5100 Flash Arrays (holding the target file set and logs) were shared by the four containers  for fast data retrieval.   
• Use of Solaris Containers highlights the consolidation of multiple web serving environments on a single server.
• Use of the Sun Ext I/O Expansion unit and Sun Storage F5100 Flash Arrays highlight the expandability of the server.
  

Disclosure Statement

Sun SPARC Enterprise T5440 (8 cores, 1 chip) 100209 SPECweb2005, was submitted to SPEC for review on October 13, 2009.  HP ProLiant DL370 G6 (8 cores, 2 chips) 83,073 SPECweb2005. HP ProLiant DL585 G5 (16 cores, 4 chips) 71,629 SPECweb2005. HP ProLiant DL580 G5 (24 cores, 4 chips) 50,013 SPECweb2005. SPEC, SPECweb reg tm of Standard Performance Evaluation Corporation. Results from www.spec.org as of Oct 10, 2009.

The Sun SPARC Enterprise M4000 server combined with Sun FlashFire technology, the Sun Storage F5100 flash array, has produced World Record Performance on PeopleSoft Payroll (North America) 9.0 benchmark.

• A Sun SPARC Enterprise M4000 server with four new 2.53GHz SPARC64 VII processors and a Sun Storage F5100 flash array is 33% faster than the HP rx6600 (4 x 1.6GHz Itanium2 processors) on the PeopleSoft Payroll (NA) 9.0 benchmark. The Sun solution used the Oracle 11g database running on Solaris 10.

• The Sun SPARC Enterprise M4000 server with four 2.53GHz SPARC64 VII processors and the Sun Storage F5100 flash array is 35% faster than the 2027 MIPs IBM Z990 (6 Z990 Gen1 processors) on the PeopleSoft Payroll (NA) 9.0 benchmark with Oracle 11g database running on Solaris 10. The IBM result used IBM DB2 for Z/OS 8.1 for the database.

• The Sun SPARC Enterprise M4000 server with four 2.53GHz SPARC64 VII processors and a Sun Storage F5100 flash array processed 250K employee payroll checks using PeopleSoft Payroll (NA) 9.0 and Oracle 11g running on Solaris 10. Four different execution strategies were run with an average improvement of 25% compared to HP's results run on the rx6600. Sun achieved these results with 8 concurrent jobs using only 25% CPU utilization while HP required 16 concurrent jobs with a 88% CPU utilization.
  

• The Sun SPARC Enterprise M4000 server combined with Sun FlashFire technology processed 8 Sequential Jobs and single run control with a total time of 527.85 mins, an improvement of 20% compared to HPs time of 633.09 mins.

• The Sun SPARC Enterprise M4000 server combined with Sun FlashFire technology demonstrated a speedup of 81% going from 1 to 8 streams on the PeopleSoft Payroll (NA) 9.0 benchmark using the Oracle 11g database.

• The Sun FlashFire technology dramatically improves IO performance for the PeopleSoft Payroll benchmark with significant performance boost over best optimized FC disks (60+).

• The Sun Storage F5100 Flash Array is a high performance high density solid state flash array which provides a read latency of only 0.5 msec which is about 10 times faster than the normal disk latencies 5 msec measured on this benchmark.

• Sun estimates that the MIPS rating for a Sun SPARC Enterprise M4000 server is over 2742 MIPS.

Performance Landscape

250K Employees

System	Processor	OS/Database	Time in Minutes			Version
			Run 1	Run 2	Run 3
Sun M4000	4x 2.53GHz SPARC64 VII	Solaris/Oracle 11g	79.35	288.47	527.85	9.0
HP rx6600	4x 1.6GHz Itanium2	HP-UX/Oracle 11g	81.17	350.16	633.25	9.0
IBM Z990	6x Gen1 2027 MIPS	Z/OS /DB2	107.34	328.66	544.80	9.0
HP rx6600	4x 1.6GHz Itanium2	HP-UX/Oracle 11g	105.70	369.59	633.09	9.0

Note: IBM benchmark documents show that 6 Gen1 procs is 2027 mips. 13 Gen1 processors were in this config but only 6 were available for testing.

500K Employees

System	Processor	OS/Database	Time in Minutes			Version
			Run 1	Run 2	Run 3
HP rx7640	8x 1.6GHz Itanium2	HP-UX/Oracle 11g	133.63	712.72	1665.01	9.0

Results and Configuration Summary

Hardware Configuration:

1 x Sun SPARC Enterprise M4000 (4 x 2.53 GHz/32GB)
1 x Sun Storage F5100 Flash Array (40 x 24GB FMODs)
1 x Sun Storage J4200 (12 x 450GB SAS 15K RPM)

Software Configuration:

Solaris 10 5/09
Oracle PeopleSoft HCM 9.0
Oracle PeopleSoft Enterprise (PeopleTools) 8.49
Micro Focus Server Express 4.0 SP4
Oracle RDBMS 11.1.0.7 64-bit
HP's Mercury Interactive QuickTest Professional 9.0

Benchmark Description

The PeopleSoft 9.0 Payroll (North America) benchmark is a performance benchmark established by PeopleSoft to demonstrate system performance for a range of processing volumes in a specific configuration. This information may be used to determine the software, hardware, and network configurations necessary to support processing volumes. This workload represents large batch runs typical of OLTP workloads during a mass update.

To measure five application business process run times for a database representing large organization. The five processes are:

• Paysheet Creation: generates payroll data worksheet for employees, consisting of std payroll information for each employee for given pay cycle.

• Payroll Calculation: Looks at Paysheets and calculates checks for those employees.

• Payroll Confirmation: Takes information generated by Payroll Calculation and updates the employees' balances with the calculated amounts.

• Print Advice forms: The process takes the information generated by payroll Calculations and Confirmation and produces an Advice for each employee to report Earnings, Taxes, Deduction, etc.

• Create Direct Deposit File: The process takes information generated by above processes and produces an electronic transmittal file use to transfer payroll funds directly into an employee bank a/c.

For the benchmark, we collect at least four data points with different number of job streams (parallel jobs). This batch benchmark allows a maximum of eight job streams to be configured to run in parallel.

Key Points and Best Practices

• Why Sun Storage F5100 is a good option for Peoplesoft NA Payroll Application

• Accelerate your Payroll Performance with F20 PCIe Card

See Also

• PeopleSoft White Papers

Disclosure Statement

Oracle PeopleSoft Payroll (NA) 9.0 benchmark, Sun M4000 (4 2.53GHz SPARC64) 79.35 min, IBM Z990 (6 gen1) 107.34 min, HP rx6600 (4 1.6GHz Itanium2) 105.70 min, www.oracle.com/apps_benchmark/html/white-papers-peoplesoft.html Results 10/13/2009.

Significance of Results

The Sun Storage F5100 Flash Array can double performance over internal hard disk drives as shown by the I/O intensive MSC/Nastran MCAE application MDR3 benchmark tests on a Sun Fire X4270 server.

The MD Nastran MDR3 benchmarks were run on a single Sun Fire X4270 server. The I/O intensive test cases were run at different core levels from one up to the maximum of 8 available cores in SMP mode.

The MSC/Nastran MD 2008 R3 module is an MCAE application based on the finite element method (FEA) of analysis. This computer based numerical method inherently involves a substantial I/O component. The purpose was to evaluate the performance of the Sun Storage F5100 Flash Array relative to high performance 15K RPM internal stripped HDDs.

• The Sun Storage F5100 Flash Array outperformed the high performance 15K RPM SAS drives on the "xx0cmd2" test case by 107% in the 8-core server configuration.

• The Sun Storage F5100 Flash Array outperformed the high performance 15K RPM SAS drives on the "xl0tdf1"test case by 85% in the 8-core server configuration.

The MD Nastran MDR3 test suite was designed to include some very I/O intensive test cases albeit some are not very scalable. These cases are the called "xx0wmd0" and "xx0xst0". Both were run and results are presented using a single core server configuration.

• The Sun Storage F5100 Flash Array outperformed the high performance 15K RPM SAS drives on the "xx0xst0"test case by 33% in the single-core server configuration.

• The Sun Storage F5100 Flash Array outperformed the high performance 15K RPM SAS drives on the "xx0wmd0"test case by 20% in the single-core server configuration.

Performance Landscape

MD Nastran MDR3 Benchmark Tests

Results in seconds

Test Case	DMP	4x15K RPM 72 GB SAS HDD striped HW RAID0	Sun F5100 r/w buff 4096 striped	Sun F5100 Performance Advantage
xx0cmd2	8	959	463	107%
xl0tdf1	8	1104	596	85%
xx0xst0	1	1307	980	33%
xx0wmd0	1	20250	16806	20%

Results and Configuration Summary

Hardware Configuration:

Sun Fire X4270

2 x 2.93 GHz QC Intel Xeon X5570 processors
24 GB memory
4 x 72 GB 15K RPM striped (HW RAID0) SAS disks
Sun Storage F5100 Flash Array
20 x 24 GB flash modules
Intel controller

Software Configuration:

O/S: 64-bit SUSE Linux Enterprise Server 10 SP 2
Application: MSC/NASTRAN MD 2008 R3
Benchmark: MDR3 Benchmark Test Suite
HP MPI: 02.03.00.00 [7585] Linux x86-64

Benchmark Description

The benchmark tests are representative of typical MSC/Nastran applications including both SMP and DMP runs involving linear statics, nonlinear statics, and natural frequency extraction.

The MD (Multi Discipline) Nastran 2008 application performs both structural (stress) analysis and thermal analysis. These analyses may be either static or transient dynamic and can be linear or nonlinear as far as material behavior and/or deformations are concerned. The new release includes the MARC module for general purpose nonlinear analyses and the Dytran module that employs an explicit solver to analyze crash and high velocity impact conditions.

Please go here for a more complete description of the tests.

Key Points and Best Practices

• Based on the maximum physical memory on a platform the user can stipulate the maximum portion of this memory that can be allocated to the Nastran job. This is done on the command line with the mem= option. On Linux based systems where the platform has a large amount of memory and where the model does not have large scratch I/O requirements the memory can be allocated to a tmpfs scratch space file system. On Solaris X64 systems advantage can be taken of ZFS for higher I/O performance.

• The MD Nastran MDR3 test cases don't scale very well, a few not at all and the rest on up to 8 cores at best.

• The test cases for the MSC/Nastran module all have a substantial I/O component where 15% to 25% of the total run times are associated with I/O activity (primarily scratch files). The required scratch file size ranges from less than 1 GB on up to about 140 GB. Performance will be enhanced by using the fastest available drives and striping together more than one of them or using a high performance disk storage system, further enhanced as indicated here by implementing the Lustre based I/O system. High performance interconnects such as InfiniBand for inter node cluster message passing as well as I/O transfer from the storage system can also enhance performance substantially.

See Also

• MSC/Nastran Benchmark Results
• http://wikis.sun.com/display/BluePrints/Solid+State+Drives+in+HPC+-+Reducing+the+IO+Bottleneck, Sun BluePrints Online

Disclosure Statement

MSC.Software is a registered trademark of MSC. All information on the MSC.Software website is copyrighted. MD Nastran MDR3 results from http://www.mscsoftware.com and this report as of October 12, 2009.

Significance of Results

The Sun Storage F5100 Flash Array is a high performance high density solid state flash array delivering over 1.6M IOPS (4K IO) and 12.8GB/sec throughput (1M reads). The Flash Array is designed to accelerate IO-intensive applications, such as databases, at a fraction of the power, space, and cost of traditional hard disk drives. It is based on enterprise-class SLC flash technology, with advanced wear-leveling, integrated backup protection, solid state robustness, and 3M hours MTBF reliability.

• The Sun Storage F5100 Flash Array demonstrates breakthrough performance of 1.6M IOPS for 4K random reads
• The Sun Storage F5100 Flash Array can also perform 1.2M IOPS for 4K random writes
• The Sun Storage F5100 Flash Array has unprecedented throughput of 12.8 GB/sec.

Performance Landscape

Results were obtained using four hosts.

Bandwidth and IOPS Measurements

Test	Flash Modules
	80	40	20	1
Random 4K Read	1,591K IOPS	796K IOPS	397K IOPS	21K IOPS
Maximum Delivered Random 4K Write	1,217K IOPS	610K IOPS	304K IOPS	15K IOPS
Maximum Delivered 50-50 4K Read/Write	850K IOPS	426K IOPS	213K IOPS	11K IOPS
Sequential Read (1M)	12.8 GB/sec	6.4 GB/sec	3.2 GB/sec	265 MB/sec
Maximum Delivered Sequential Write (1M)	9.7 GB/sec	4.8 GB/sec	2.4 GB/sec	118 MB/sec
Sustained Random 4K Write*	311K IOPS	169K IOPS	86K IOPS	4.4K IOPS

(*) Maximum Delivered values measured over a 1 minute period. Sustained write performance differs from maximum delivered performance. Over time, wear-leveling and erase operations are required and impact write performance levels.

Latency Measurements

The Sun Storage F5100 Flash Array is tuned for 4 KB or larger IO sizes, the write service for IOs smaller than 4 KB can be 10 times more than shown in the table below. It should also be noted that the service times shown below are both the latency and the time to transfer the data. This becomes the dominant portion the the service time for IOs over 64 KB in size.

Transfer Size	Service Time (ms)
	Read	Write
4 KB	0.41	0.28
8 KB	0.42	0.35
16 KB	0.45	0.72
32 KB	0.51	0.77
64 KB	0.63	1.52
128 KB	0.87	2.99
256 KB	1.34	6.03
512 KB	2.29	12.14
1024 KB	4.19	23.79

- Latencies are measured application latencies via vdbench tool.
- Please note that the F5100 Flash Array is a 4KB sector device. Doing IOs of less than 4KB in size, or not aligned on 4KB boundaries, can result in a significant performance degradations on write operations.

Results and Configuration Summary

Storage:

Sun Storage F5100 Flash Array

80 Flash Modules
16 ports
4 domains (20 Flash Modules per)
CAM zoning - 5 Flash Modules per port

Servers:

4 x Sun SPARC Enterprise T5240
4 x 4 HBAs each, firmware version 01.27.03.00-IT

Software:

OpenSolaris 2009.06 or Solaris 10 10/09 (MPT driver enhancements)
Vdbench 5.0
Required Flash Array Patches SPARC, ses/sgen patch 138128-01 or later & mpt patch 141736-05
Required Flash Array Patches x86, ses/sgen patch 138129-01 or later & mpt patch 141737-05

Benchmark Description

Sun measured a wide variety of IO performance metrics on the Sun Storage F5100 Flash Array using Vdbench 5.0 measuring 100% Random Read, 100% Random Write, 100% Sequential Read, 100% Sequential Write, and 50-50 read/write. This demonstrates the maximum performance and throughput of the storage system.

Vdbench profile parmfile.txt here

Vdbench is publicly available for download at: http://vdbench.org

Key Points and Best Practices

• Drive each Flash Modules with 32 outstanding IO as shown in the benchmark profile above.
• LSI HBA firmware level should be at Phase 15 maxq.
• LSI HBAs either use single port HBAs or only 1 port per HBA.
• SPARC platforms will align with the 4K boundary size set by the Flash Array. x86/windows platforms don't necessarily have this alignment built in and can show lower performance

See Also

• Vdbench is publicly available for download at: http://vdbench.org
• Firmware obtained from http://www.lsi.com/support/sun

Disclosure Statement

Sun Storage F5100 Flash Array delivered 1.6M 4K read IOPS and 12.8 GB/sec sequential read. Vdbench 5.0 (http://vdbench.org) was used for the test. Results as of September 12, 2009.

TPC-C Sun SPARC Enterprise T5440 with Oracle RAC World Record Database Result

Sun and Oracle demonstrate the World's fastest database performance. Sun Microsystems using 12 Sun SPARC Enterprise T5440 servers, 60 Sun Storage F5100 Flash arrays and Oracle 11g Enterprise Edition with Real Application Clusters and Partitioning delivered a world-record TPC-C benchmark result.

• The 12-node Sun SPARC Enterprise T5440 server cluster result delivered a world record TPC-C benchmark result of 7,646,486.7 tpmC and $2.36 $/tpmC (USD) using Oracle 11g R1 on a configuration available 12/14/09.

• The 12-node Sun SPARC Enterprise T5440 server cluster beats the performance of the IBM Power 595 (5GHz) with IBM DB2 9.5 database by 26% and has 16% better price/performance on the TPC-C benchmark.

• The complete Oracle/Sun solution used 10.7x better computational density than the IBM configuration (computational density = performance/rack).

• The complete Oracle/Sun solution used 8 times fewer racks than the IBM configuration.

• The complete Oracle/Sun solution has 5.9x better power/performance than the IBM configuration.

• The 12-node Sun SPARC Enterprise T5440 server cluster beats the performance of the HP Superdome (1.6GHz Itanium2) by 87% and has 19% better price/performance on the TPC-C benchmark.

• The Oracle/Sun solution utilized Sun FlashFire technology to deliver this result. The Sun Storage F5100 flash array was used for database storage.

• Oracle 11g Enterprise Edition with Real Application Clusters and Partitioning scales and effectively uses all of the nodes in this configuration to produce the world record performance.

• This result showed Sun and Oracle's integrated hardware and software stacks provide industry-leading performance.

More information on this benchmark will be posted in the next several days.

Performance Landscape

TPC-C results (sorted by tpmC, bigger is better)

System	tpmC	Price/tpmC	Avail	Database	Cluster	Racks	w/KtpmC
12 x Sun SPARC Enterprise T5440	7,646,487	2.36 USD	12/14/09	Oracle 11g RAC	Y	9	9.6
IBM Power 595	6,085,166	2.81 USD	12/10/08	IBM DB2 9.5	N	76	56.4
Bull Escala PL6460R	6,085,166	2.81 USD	12/15/08	IBM DB2 9.5	N	71	56.4
HP Integrity Superdome	4,092,799	2.93 USD	08/06/07	Oracle 10g R2	N	46	to be added

Avail - Availability date
w/KtmpC - Watts per 1000 tpmC
Racks - clients, servers, storage, infrastructure

Results and Configuration Summary

Hardware Configuration:

9 racks used to hold

Servers:

12 x Sun SPARC Enterprise T5440
4 x 1.6 GHz UltraSPARC T2 Plus
512 GB memory
10 GbE network for cluster

Storage:

60 x Sun Storage F5100 Flash Array
61 x Sun Fire X4275, Comstar SAS target emulation
24 x Sun StorageTek 6140 (16 x 300 GB SAS 15K RPM)
6 x Sun Storage J4400
3 x 80-port Brocade FC switches

Clients:

24 x Sun Fire X4170, each with
2 x 2.53 GHz X5540
48 GB memory

Software Configuration:

Solaris 10 10/09
OpenSolaris 6/09 (COMSTAR) for Sun Fire X4275
Oracle 11g Enterprise Edition with Real Application Clusters and Partitioning
Tuxedo CFS-R Tier 1
Sun Web Server 7.0 Update 5

Benchmark Description

TPC-C is an OLTP system benchmark. It simulates a complete environment where a population of terminal operators executes transactions against a database. The benchmark is centered around the principal activities (transactions) of an order-entry environment. These transactions include entering and delivering orders, recording payments, checking the status of orders, and monitoring the level of stock at the warehouses.

POSTSCRIPT: Here are some comments on IBM's grasping-at-straws-perf/core attacks on the TPC-C result:
c0t0d0s0 blog: "IBM's Reaction to Sun&Oracle TPC-C

See Also

• TPC-C Official Result Page
  

• www.tpc.org Website

Disclosure Statement

TPC Benchmark C, tpmC, and TPC-C are trademarks of the Transaction Performance Processing Council (TPC). 12-node Sun SPARC Enterprise T5440 Cluster (1.6GHz UltraSPARC T2 Plus, 4 processor) with Oracle 11g Enterprise Edition with Real Application Clusters and Partitioning, 7,646,486.7 tpmC, $2.36/tpmC. Available 12/14/09. IBM Power 595 (5GHz Power6, 32 chips, 64 cores, 128 threads) with IBM DB2 9.5, 6,085,166 tpmC, $2.81/tpmC, available 12/10/08. HP Integrity Superdome(1.6GHz Itanium2, 64 processors, 128 cores, 256 threads) with Oracle 10g Enterprise Edition, 4,092,799 tpmC, $2.93/tpmC. Available 8/06/07. Source: www.tpc.org, results as of 10/11/09.

Significance of Results

The Sun SSD (32 GB SATA 2.5" SSD) is the world's first enterprise-quality, open-standard Flash design. Built to an industry-standard JEDEC form factor, the module is being made available to developers and the OpenSolaris Storage community to foster Flash innovation. The Sun SSD delivers unprecedented IO performance, saves on power, space, and cooling, and will enable new levels of server optimization and datacenter efficiencies.

• The Sun SSD demonstrated performance of 98K 4K random read IOPS on a Sun Fire X4450 server running the Solaris operating system.

Performance Landscape

Solaris 10 Results

Test	SSD Result
	X4450	X4140/X4440	T5240
Random Read (4K)	98.4K IOPS	33.8K IOPS	71.5K IOPS
Random Write (4K)	31.8K IOPS	16.6K IOPS	14.4K IOPS
50-50 Read/Write (4K)	14.9K IOPS	13.3K IOPS	15.7K IOPS
Sequential Read (MB/sec)	764 MB/sec	463 MB/sec	1012 MB/sec
Sequential Write (MB/sec)	376 MB/sec	470 MB/sec	531 MB/sec

Windows 2003 Server Results

Test	SSD Result
	X4140	X4440
Random Read (4K)	66.9K IOPS	63.1K IOPS
Random Write (4K)	17.6K IOPS	29.7K IOPS
50-50 Read/Write (4K)	14.9K IOPS	16.9K IOPS
Sequential Read (MB/sec)	832 MB/sec	844 MB/sec
Sequential Write (MB/sec)	121 MB/sec	408 MB/sec

Results and Configuration Summary

Storage:

4 x Sun SSD
32 GB SATA 2.5" SSD (24 GB usable)
2.5in drive form factor

Servers:

Sun SPARC Enterprise T5240 - 4 internal drive slots used (LSI driver)
Sun Fire X4450 - 4 internal drive slots used (LSI driver)
Sun Fire X4440 - 4 internal drive slots used (LSI driver)
Sun Fire X4140 - 4 internal drive slots used (LSI driver)

Software:

Window 2003 Server
OpenSolaris 2009.06 or Solaris 10 10/09 (MPT driver enhancements)
Vdbench 5.0

Benchmark Description

Sun measured a wide variety of IO performance metrics on the Sun SSD using Vdbench 5.0 measuring 100% Random Read, 100% Random Write, 100% Sequential Read, 100% Sequential Write, and 50-50 read/write. This demonstrates the maximum performance and throughput of the storage system.

Vdbench profile:

wd=wm_80dr,sd=sd*,readpct=0,rhpct=0,seekpct=100
wd=ws_80dr,sd=sd*,readpct=0,rhpct=0,seekpct=0
wd=rm_80dr,sd=(sd1-sd80),readpct=100,rhpct=0,seekpct=100
wd=rs_80dr,sd=(sd1-sd80),readpct=100,rhpct=0,seekpct=0
wd=rwm_80dr,sd=sd*,readpct=50,rhpct=0,seekpct=100
rd=default
###Random Read and writes tests varying transfer size
rd=default,el=30m,in=6,forx=(4K),forth=(32),io=max,pause=20
rd=run1_rm_80dr,wd=rm_80dr
rd=run2_wm_80dr,wd=wm_80dr
rd=run3_rwm_80dr,wd=rwm_80dr
###Sequential read and Write tests varying transfer size
rd=default,el=30m,in=6,forx=(512k),forth=(32),io=max,pause=20
rd=run4_rs_80dr,wd=rs_80dr
rd=run5_ws_80dr,wd=ws_80dr

Vdbench is publicly available for download at: http://vdbench.org

Key Points and Best Practices

• All measurements were done with the internal HBA and not the internal RAID.

See Also

• Vdbench is publicly available for download at: http://vdbench.org

Disclosure Statement

Sun SSD delivered 71.5K 4K read IOPS and 1012 MB/sec sequential read. Vdbench 5.0 (http://vdbench.org) was used for the test. Results as of June 17, 2009.

High-Performance Computing (HPC) applications can be dramatically increased by simply using SSDs instead of traditional hard drives. To read about these findings see the Sun BluePrint by Larry McIntosh and Michael Burke, called "Solid State Drives in HPC: Reducing the I/O Bottleneck".

There was a BestPerf blog posting on the NASTRAN/SSD results at:
http://blogs.sun.com/BestPerf/entry/sun_fire_x2270_msc_nastran

Our BestPerf authors will blog about more of their recent benchmarks in the coming weeks.

Significance of Results

The I/O intensive MSC/Nastran Vendor_2008 benchmark test suite was used to compare the performance on a Sun Fire X2270 server when using SSDs internally instead of HDDs.

The effect on performance from increasing memory to augment I/O caching was also examined. The Sun Fire X2270 server was equipped with Intel QC Xeon X5570 processors (Nehalem). The positive effect of adding memory to increase I/O caching is offset to some degree by the reduction in memory frequency with additional DIMMs in the bays of each memory channel on each cpu socket for these Nehalem processors.

• SSDs can significantly improve NASTRAN performance especially on runs with larger core counts.
• Additional memory in the server can also increase performance, however in some systems additional memory can decrease memory GHz so this may offset the benefits of increased capacity.
• If SSDs are not used striped disks will often improve performance of IO-bound MCAE applications.
• To obtain the highest performance it is recommended that SSDs be used and servers be configured with the largest memory possible without decreasing memory GHz. One should always look at the workload characteristics and compare against this benchmark to correctly set expectations.

SSD vs. HDD Performance

The performance of two striped 30GB SSDs was compared to two striped 7200 rpm 500GB SATA drives on a Sun Fire X2270 server.

• At the 8-core level (maximum cores for a single node) SSDs were 2.2x faster for the larger xxocmd2 and the smaller xlotdf1 cases.
• For 1-core results SSDs are up to 3% faster.
• On the smaller mdomdf1 test case there was no increase in performance on the 1-, 2-, and 4-cores configurations.

Performance Enhancement with I/O Memory Caching

Performance for Nastran can often be increased by additional memory to provide additional in-core space to cache I/O and thereby reduce the IO demands.

The main memory was doubled from 24GB to 48GB. At the 24GB level one 4GB DIMM was placed in the first bay of each of the 3 CPU memory channels on each of the two CPU sockets on the Sun Fire X2270 platform. This configuration allows a memory frequency of 1333MHz.

At the 48GB level a second 4GB DIMM was placed in the second bay of each of the 3 CPU memory channels on each socket. This reduces the memory frequency to 1066MHz.

Adding Memory With HDDs (SATA)

• The additional server memory increased the performance when running with the slower SATA drives at the higher core levels (e.g. 4- & 8-cores on a single node)
• The larger xxocmd2 case was 42% faster and the smaller xlotdf1 case was 32% faster at the maximum 8-core level on a single system.
• The special I/O intensive getrag case was 8% faster at the 1-core level.

Adding Memory With SDDs

• At the maximum 8-core level (for a single node) the larger xxocmd2 case was 47% faster in overall run time.
• The effects were much smaller at lower core counts and in the tests at the 1-core level most test cases ran from 5% to 14% slower with the slower CPU memory frequency dominating over the added in-core space available for I/O caching vs. direct transfer to SSD.
• Only the special I/O intensive getrag case was an exception running 6% faster at the 1-core level.

Increasing performance with Two Striped (SATA) Drives

The performance of multiple striped drives was also compared to single drive. The study compared two striped internal 7200 rpm 500GB SATA drives to a singe single internal SATA drive.

• On a single node with 8 cores, the largest test xx0cmd2 was 40% faster, a smaller test case xl0tdf1 was 33% faster and even the smallest test case mdomdf1 case was 12% faster.

• On 1-core the added boost in performance with striped disks was from 4% to 13% on the various test cases.

• One 1-core the special I/O-intensive test case getrag was 29% faster.

Performance Landscape

Times in table are elapsed time (sec).

MSC/Nastran Vendor_2008 Benchmark Test Suite
Test	Cores	Sun Fire X2270 2 x X5570 QC 2.93 GHz 2 x 7200 RPM SATA HDDs					Sun Fire X2270 2 x X5570 QC 2.93 GHz 2 x SSDs
		48 GB 1067MHz	24 GB 2 SATA 1333MHz	24 GB 1 SATA 1333MHz	Ratio (2xSATA): 48GB/ 24GB	Ratio: 2xSATA/ 1xSATA	48 GB 1067MHz	24 GB 1333MHz	Ratio: 48GB/ 24GB	Ratio (24GB): 2xSATA/ 2xSSD
vlosst1	1	133	127	134	1.05	0.95	133	126	1.05	1.01
xxocmd2	1 2 4 8	946 622 466 1049	895 614 631 1554	978 703 991 2590	1.06 1.01 0.74 0.68	0.87 0.87 0.64 0.60	947 600 426 381	884 583 404 711	1.07 1.03 1.05 0.53	1.01 1.05 1.56 2.18
xlotdf1	1 2 4 8	2226 1307 858 912	2000 1240 833 1562	2081 1308 1030 2336	1.11 1.05 1.03 0.58	0.96 0.95 0.81 0.67	2214 1315 744 674	1939 1189 751 712	1.14 1.10 0.99 0.95	1.03 1.04 1.11 2.19
xloimf1	1	1216	1151	1236	1.06	0.93	1228	1290	0.95	0.89
mdomdf1	1 2 4	987 524 270	913 485 237	983 520 269	1.08 1.08 1.14	0.93 0.93 0.88	987 524 270	911 484 250	1.08 1.08 1.08	1.00 1.00 0.95
Sol400_1 (xl1fn40_1)	1	2555	2479	2674	1.03	0.93	2549	2402	1.06	1.03
Sol400_S (xl1fn40_S)	1	2450	2302	2481	1.06	0.93	2449	2262	1.08	1.02
getrag (xx0xst0)	1	778	843	1178	0.92	0.71	771	817	0.94	1.03

Results and Configuration Summary

Hardware Configuration:

Sun Fire X2270

1 2-socket rack mounted server
2 x 2.93 GHz QC Intel Xeon X5570 processors
2 x internal striped SSDs
2 x internal striped 7200 rpm 500GB SATA drives

Software Configuration:

O/S: Linux 64-bit SUSE SLES 10 SP 2
Application: MSC/NASTRAN MD 2008
Benchmark: MSC/NASTRAN Vendor_2008 Benchmark Test Suite
HP MPI: 02.03.00.00 [7585] Linux x86-64
Voltaire OFED-5.1.3.1_5 GridStack for SLES 10

Benchmark Description

The benchmark tests are representative of typical MSC/Nastran applications including both SMP and DMP runs involving linear statics, nonlinear statics, and natural frequency extraction.

The MD (Multi Discipline) Nastran 2008 application performs both structural (stress) analysis and thermal analysis. These analyses may be either static or transient dynamic and can be linear or nonlinear as far as material behavior and/or deformations are concerned. The new release includes the MARC module for general purpose nonlinear analyses and the Dytran module that employs an explicit solver to analyze crash and high velocity impact conditions.

• As of the Summer '08 there is now an official Solaris X64 version of the MD Nastran 2008 system that is certified and maintained.
• The memory requirements for the test cases in the new MSC/Nastran Vendor 2008 benchmark test suite range from a few hundred megabytes to no more than 5 GB.

Please go here for a more complete description of the tests.

Key Points and Best Practices

For more on Best Practices of SSD on HPC applications also see the Sun Blueprint:
http://wikis.sun.com/display/BluePrints/Solid+State+Drives+in+HPC+-+Reducing+the+IO+Bottleneck

Additional information on the MSC/Nastran Vendor 2008 benchmark test suite.

• Based on the maximum physical memory on a platform the user can stipulate the maximum portion of this memory that can be allocated to the Nastran job. This is done on the command line with the mem= option. On Linux based systems where the platform has a large amount of memory and where the model does not have large scratch I/O requirements the memory can be allocated to a tmpfs scratch space file system. On Solaris X64 systems advantage can be taken of ZFS for higher I/O performance.

• The MSC/Nastran Vendor 2008 test cases don't scale very well, a few not at all and the rest on up to 8 cores at best.

• The test cases for the MSC/Nastran module all have a substantial I/O component where 15% to 25% of the total run times are associated with I/O activity (primarily scratch files). The required scratch file size ranges from less than 1 GB on up to about 140 GB. Performance will be enhanced by using the fastest available drives and striping together more than one of them or using a high performance disk storage system, further enhanced as indicated here by implementing the Lustre based I/O system. High performance interconnects such as Infiniband for inter node cluster message passing as well as I/O transfer from the storage system can also enhance performance substantially.

See Also

• Current MSC/Nastran Vendor 2008 results

Disclosure Statement

MSC.Software is a registered trademark of MSC. All information on the MSC.Software website is copyrighted. MSC/Nastran Vendor 2008 results from http://www.mscsoftware.com and this report as of June 9, 2009.