Currently Available Facilities and Tools at CCL

 

CCL currently occupies about 700 square feet in two primary rooms of the Environmental and Occupational Health Sciences Institute, located on Busch Campus of Rutgers University in Piscataway, New Jersey. Complete and frequently updated lists of various resources and software, for which CCL maintains active licenses, are available on the following pages:

eohsiBuilding

The Computational Chemodynamics Laboratory (CCL) at the Environmental and Occupational Health Sciences Institute (EOHSI) is a state-of-the-art facility for modeling and informatics of environmental and biological systems, dedicated to the development and improvement of methods for performing mechanistically-based health risk studies.

CCL provides the resources for the Informatics and Computational Toxicology (ICT) Core of the NIEHS-funded Center for Environmental Exposures and Disease (CEED).  CCL supports, through modeling and data analysis, the environmental bioinformatics and Computational Toxicology Center (ebCTC) and the Center for Exposure and Risk Modeling (CERM). It also supports the Ozone Research Center, funded by the New Jersey Department of Environmental Protection (NJDEP); the NIOSH-sponsored Cancer Among WTC Responders – Enhanced Surveillance, Exposure Assessment, and Cancer Specific Risk project (with Mount Sinai School of Medicine); the Respiratory Effects of Silver and Carbon Nanomaterials (RESAC) Center, funded by NIEHS; the Climate Change and Allergic Airway Disease (CCAAD); and the Risk Assessment for Manufactured Nanoparticles Used in Consumer Products (RAMNUC) projects, funded by USEPA.

CCL maintains a distributed networked computing system optimized for scientific analysis of large data sets and for complex mechanistic model simulations. This system currently incorporates five (5) clusters of multiprocessor Sun/Oracle (Solaris) and Beowulf (Linux) multicore servers supporting parallel computing, complemented by personal workstations (with Mac, Windows, and Linux operating systems) running Network File System (NFS and SMBFS) over a local switched gigabit ethernet-based LAN. Specifically, the five clusters mentioned above consist of (i) a 16-node cluster with 32 GB RAM, (ii) a 16-core system with 64 GB RAM, (iii) a 48-core system with 128 GB RAM, and (iv and v) two 64-core systems with 512 GB RAM, each with several terabytes of fast disk storage used for large scale simulations. So, overall the local computing facilities at CCL span over 50 servers and over 20 workstations that access a total of more than 260 terabytes of internal hard disk space with RAID protection.

The CCL computing clusters can operate in flexible modes, either as batch processors for multiple simulations assigned by front-load balancers, or as shared memory parallel virtual machines employing the Message Passing Interface (MPI) system. The combination of server-client and cluster computing approaches utilizing multiple operating systems assures both flexibility and cost-effectiveness in relation to either employing commercial and open source software for analysis or implementing locally developed applications. This hardware structure is particularly cost-effective for performing large-scale sensitivity and uncertainty studies, “big data” analyses, and optimization for complex multiscale/multilevel modeling studies.

CCL also employs resources for graphics and visualization capabilities through various Mac, Windows, and Linux workstations, several of which are bootable to two or more operating systems. Researchers also use high-end, dual bootable laptops with wireless connectivity and secure, remote access. Various peripherals, including multipurpose copier/printer/scanner machines and a large format printer, complement the network and provide support for a wide range of operating systems, data types and formats.

The organization of the computational resources at CCL is based on the rationale of using the right tool for the task, as well as making the tools function robustly in a multitude of computing environments, including grid computing. The software tools and databases developed at CCL are routinely tested on multiple platforms (Windows, Linux, Mac, and, in certain cases, on mobile devices running on iOS and Android), and are typically developed with cross-platform compatibility as one of the primary goals (in addition to correctness, robustness, efficiency, and ease of use via web-based interfaces whenever possible). All computer model development as well as documentation and reporting follow standardized policies that focus on version control and accessing of documentation and computer code (via RCS and CVS version control systems, which are also usable via CCL’s secure intranet), standardized evaluation procedures for existing tools and methods, and standardized reporting and tracking of feature requests, issues and bugs in the computational tools developed (via web-based interfaces using open source tools for bug tracking and reporting). Partial off-site data backup provides an added layer of security.

CCL Software Facilities

To assure usage of state-of-the-art approaches for model development and data analysis, CCL maintains both open source tools and locally active licenses for a wide range of commercial software, including tools for Relational Database Development and Management (including MySQL, FileMaker Pro, Oracle, PostgreSQL, MS Access etc.), Geographic Information Systems analysis (including ArcGIS, GRASS, RAMAS GIS, PostGIS, Google Earth Pro, etc.), cheminformatics and bioinformatics/toxicoinformatics methods and “big data analytics” (including Hadoop/MapReduce/HBase and MongoDB, etc.), computational simulation techniques for “people analytics” (including Matlab, Python, R, ArcGIS, and REPAST, etc.), numerical and analytical model coding (including Matlab, Mathematica, Maple, acslX, MathCad, Octave, etc., as well as Fortran, C/C++/Objective C, Python, Perl, Java, Visual Studio, and Titanium development environments), Computational Fluid Dynamics (CFD) (including Ansys CFD, OpenFOAM, Phoenics, MultiPhysics, STAR-CD, etc.), data visualization (including TecPlot, NCAR Graphics, EVS Pro, ParaView, etc.), statistical analysis and data mining (including SAS [with SAS Enterprise Miner – SAS-EM], R, SPSS [with the SPSS Modeler data mining package], Statistica [with Data and Text Miner], S-Plus, SYSTAT, etc.), visual model development (including Rational Rose, Stella, Simul8, SimuLink, etc.), engineering design and technical illustration (including AutoCad, Visio Pro, Sketch-Up Pro, 3D Studio Viz), image processing (including GIMP, Photoshop, Illustrator, Matlab Image Processing, etc.), and website and web-based application development (including Dreamweaver, PHP, CSS3, HTML5, ArcIMS, open source CMS, etc.).

CCL Environmental and Biological Models, Databases and Supplemental Resources

CCL maintains up-to-date versions of a wide range of environmental and biological modeling packages for atmospheric, multimedia, and physiological applications, plus numerous extant databases that are currently linked with the MENTOR and PRoTEGE systems for CCL’s Exposure Information Systems (EXIS). Examples of these resources are listed in multiple, searchable, categorized tables on the Environmental Bioinformatics Knowledge Base (ebKB) website.


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