Software For Download

The molecular dynamics (MD) code for GPU Fen Zi (yun dong de FEN ZI in Mandarin or moving MOLECULES in English) is now available in GitHub. Download the code here.

The QCN Explorer source to learn how to monitor earthquakes with low-cost accelerometers connected to volunteer computers is now availabe in GitHub. Download the code here.

The D@H screensaver source is now available in Google Code. Download the code here.

Web Applications

Play with QCN Explorer and learn how to use low-cost accelerometers to monitor earthquake everywhere in the world by visiting QCNExplorer.

Current Research Projects

Volunteer Computing:
Docking@Home: Dynamically adaptive protein-ligand docking system using volunteer computing
Docking@Home Screensaver: Docking@Home screensaver and graphical application for Volunteer Computing Projects studying molecular systems.
EmBOINC: An Emulator for BOINC Applications

GPU Programming and Scientific Applications:
FEN ZI (yun dong de FEN ZI = Moving MOLECULES) a CUDA code that enables large-scale, GPU-based MD simulations using the CHARMM force field. In FEN ZI, the complete MD simulation is performed on GPUs.
DACAPO GPUs - Developing Applications for Computer Architectures based on Parallel Organizations of GPUs: Use the computing power of parallel GPUs for scientific applications, e.g., Molecular Dynamics and Monte Carlo simulations (web-page under construction)

Grid Computing:
jTopaz: A friendly, open-source GridFTP protocol extension to the Firefox browser for accessing grid repositories

Bioinformatics:
RNAVLab: An open-source user-friendly virtual Laboratory for RNA secondary structure predictions
Pseudobase++: A searchable up-to-date database of the PseudoBase pseudoknots wrapped by a versatile, user-friendly interface providing scientists with a powerful engine to access, search, select, and sort data based on different fine-grained criteria

Our Research Equipment

Our laboratory is equipped for studying scientific applications on multi-core and GPU platforms. We have access to several clusters at the University of Delaware and high-end workstations in our lab.

Dr. Taufer was awarded an NSF Major Research Instrumentation (MRI) award (CHE-0922657). The NSF award supported the acquisition of a hybrid-computing cluster in 2011 with GPU-accelerated computing nodes. The cluster includes 48 dual six-core compute nodes (576 cores), 96 Fermi S2070 GPU systems. Two front-end nodes for compilation and workload management as well as a 20 TByte storage system are connected to the compute nodes. The cluster utilizes both an Infiniband fabric and a Gigabit Ethernet interconnect. The GPU-enabled capacity of the cluster supports implementation and testing of HPC research involving multi-threading GPU programming in scientific computing. The cluster also supports a large number of theoretical and experimental researchers at UD to study a number of problems in the chemical sciences. Our equipment resources include a small high-end cluster comprising of:

  1. A dual quad-core compute nodes (48 cores) and 3 Tesla S1060 GPU systems with 4 GPUs per Tesla, 12 GPU total. Each Tesla system is connected to two compute nodes.
  2. A dual quad-core compute nodes (16 cores) each hosting 4 Fermi C2050 GPUs, 8 GPU total.
A front-end node is connected to the compute nodes and is used for compilation and job submissions. A high-speed DDR Infiniband interconnect for application and I/O traffic and a Gigabit Ethernet interconnect for management traffic connects the compute and front-end nodes. In our lab we work with high-end dual quad-core workstations, each hosting two GPUs, either NVIDIA GeForce GTX480, or GTX 580 (Fermi).

Past Projects

SHiPPER: Spreading High-Performance computing Participation in undergraduate Education and Research (Old web-page at UTEP - page no longer maintained by M. Taufer)
MSM Consortium - Working Group 5: Working Group targeting topics in high-performance computing, computational issues, and algorithms
Predictor@home: Protein structure predictions using volunteer computing (TSRI site)