Biometrics - Equipment
Hardware: Each biostatistician and data analyst has a Microsoft Windows-based desktop or laptop personal computer with a Windows XP processor, at least 100GB hard drive memory space, and a CD/DVD drive. The Biometrics Shared Resource has three UNIX workstations running Solaris 8 operating systems:
- Sun Blade 2000 with two UltraSPARC III Cu 1.05 GHz CPUs with 8-MB External Cache per processor, 4GB memory and 146GB disk space
- Sun Blade 2000 with two UltraSPARC III 900 MHz CPUs with 8-MB External Cache per processor, 4GB memory and 110GB disk space
- Sun Ultra 80 with two UltraSPARC II 450 MHz CPUs with 4-MB L2 Cache per processor, 1GB memory and 18GB disk space
In addition, Biometrics added a storage disk array system: Sun StorageTek T 6140 array with 4GB cache and 8 host ports, Rack-Ready Controller Tray, 2500GB, (5 X 500GB 7.2Krpm SATA-II Drives) and a Dell Precision T7500 32bit Dual Processor as a web server to implement an internet accessible centralized randomization program.
The UNIX workstations are located at the Cancer Institute and are connected to the university network so that authorized users can access them via the Internet. There is full backup daily and monthly, with incremental backups daily and each weekend. The monthly backup tapes are secured and locked off site. The combination of server-client and cluster computing approaches assures flexibility and cost-effectiveness for using commercial software for analyses and for implementing locally developed applications. This hardware structure is capable of processing and manipulating large data sets and performing computing-intensive data analyses and simulations. It is particularly cost-effective for performing large-scale data management and complex exploratory research in bioinformatics.
Software: In addition to the standard package of Microsoft Office for Windows XP for PCs, other statistical and numerical analysis software packages and compilers are installed on the UNIX machines, including SAS, R, and FORTRAN. The Biometrics faculty and staff develop their own computer programs using SAS and/or R when necessary.