Our paper describing how we implemented the Real Time System (RTS) of the Murchison Widefield Array (MWA) on GPUs has now been accepted by Computer Physics Communications, and is online at arxiv. GPU acceleration was key to this project, a demanding signal processing application.
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Our recent paper, entitled, `Accelerating correlated quantum chemistry calculations using graphical processing units’, by Mark A. Watson, Roberto Olivares-Amaya, Richard G. Edgar, Tomas Arias, and Alan Aspuru-Guzik, has been accepted for the special issue of Computing in Science and Engineering, `SI:Jul/Aug 2010 – High Performance Computing with Accelerators’. Our manuscript pre-print is available here. Downloads
On 1st February 1, 2010, Won-Ki Jeong, Research Scientist at Harvard IIC/SEAS, gave a SciGPU lunchtime seminar entitled: “GPU-accelerated Biomedical Image Analysis” Download his presentation here [20MB]. Abstract In this talk, I will introduce my past and recent research results in GPU-accelerated biomedical image analysis. Specifically, I will talk about the Fast Iterative Method, a parallel algorithm to solve a class of Hamilton-Jacobi equations for weighted distance computation and its application in DT-MRI white matter connectivity analysis. Second, I will introduce NeuroTrace, a GPU-accelerated semi-automatic segmentation and interactive visualization system for processing terabytes of electron microscopy image data, a first step toward the complete reconstruction of neural connections in the mammalian brain. About the speaker Downloads
Ron Babich from Boston University gave a talk entitled “Unraveling the Mysteries of Quarks with GPUs” for the IIC SciGPU seminar on February 22nd, 2010. Slides are available here. Downloads
Note: The application process is now closed. Thanks for your interest! SciGPU is pleased to announce summer research opportunities in scientific GPU computing for undergraduates. We seek undergraduates majoring in science and engineering who are interested in developing new algorithms and systems that use GPUs for applications in astronomy, quantum chemistry and neuroscience. Interested students may apply at www.reusite.seas.harvard.edu/application. These hands-on experiences are best suited to students with programming experience, but it is not necessary to have experience with GPUs. Participants will become part of a large, diverse research community through organized and informal interactions with students, mentors and faculty in the summer intern programs of the Harvard School of Engineering and Applied Sciences. Students participating in this year’s program, sponsored by the National Science Foundation, will spend June 6 through Aug. 14 on the Harvard campus. They will receive a stipend of $3,900 and a $300 travel allowance as well as on-campus housing at no additional charge. Information about last year’s program may be found here. Download the attached flyer for additional details. Downloads
Mark Silberstein (Technion) gave a SciGPU talk at Harvard entitled “Efficient sum-product computations on GPUs through software-managed cache” on November 23, 2009. His slides are posted here: SumProductHarvard Downloads
Dr. Peter Lu (Harvard University, Physics) recently gave a presentation to the SciGPU group based on his work outlined in the journal paper below: ———– We implement image correlation, a fundamental component of many real-time imaging and tracking systems, on a graphics processing unit (GPU) using NVIDIAs CUDA. We use our code to analyze images of liquid-gas phase separation in a model colloid-polymer system, photographed in the absence of gravity aboard the International Space Station (ISS). Our GPU code is 4000 times faster than simple MATLAB code performing the same calculation on a central processing unit (CPU), 130 times faster than simple C code, and 30 times faster than optimized C++ code using single-instruction, multiple data (SIMD) extensions. The speed increases from these parallel algorithms enable us to analyze images downlinked from the ISS in a rapid fashion and send feedback to astronauts on orbit while the experiments are still being run. Download PeterLu_BCAT_JRealTimeImageProc_2009. Quantum chemistry
Our new article, Accelerating Correlated Quantum Chemistry Calculations Using Graphical Processing Units and a Mixed Precision Matrix Multiplication Library,” by Roberto Olivares-Amaya, Mark A. Watson, Richard G. Edgar, Leslie Vogt, Yihan Shao and Alan Aspuru-Guzik, is now available online at the JCTC website: http://pubs.acs.org/doi/abs/10.1021/ct900543q Abstract Two new tools for the acceleration of computational chemistry codes using graphical processing units (GPUs) are presented. First, we propose a general black-box approach for the efficient GPU acceleration of matrix−matrix multiplications where the matrix size is too large for the whole computation to be held in the GPU’s onboard memory. Second, we show how to improve the accuracy of matrix multiplications when using only single-precision GPU devices by proposing a heterogeneous computing model, whereby single- and double-precision operations are evaluated in a mixed fashion on the GPU and central processing unit, respectively. The utility of the library is illustrated for quantum chemistry with application to the acceleration of resolution-of-the-identity second-order Møller−Plesset perturbation theory calculations for molecules, which we were previously unable to treat. In particular, for the 168-atom valinomycin molecule in a cc-pVDZ basis set, we observed speedups of 13.8, 7.8, and 10.1 times for single-, double- and mixed-precision general matrix multiply (SGEMM, DGEMM, and MGEMM), respectively. The corresponding errors in the correlation energy were reduced from −10.0 to −1.2 kcal mol−1 for SGEMM and MGEMM, respectively, while higher accuracy can be easily achieved with a different choice of cutoff parameter. Astronomy
The Murchison Widefield Array is using a real-time GPU correlator to enable engineering and early science for a 5% prototype. Read more about how this system works! See online coverage of the MWA showcasing GPU computing efficiency, as described at the NVIDIA GPU Technology Conference, San Jose 2009. Take a look at the related talk, Diesel-Power GPU Computing. Downloads
This is a poster that was recently presented at the NVIDIA GPU Technology Conference (GTC). Abstract Download: Lattice QCD poster |
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