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.
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
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)
jTopaz: A friendly, open-source GridFTP protocol extension to the Firefox browser for accessing grid repositories
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:
- 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.
- A dual quad-core compute nodes (16 cores) each hosting 4 Fermi C2050 GPUs, 8 GPU total.
Past ProjectsSHiPPER: 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)