Acquisition of Graphic-Processing-Units (GPUs) to Upgrade the CPU Cluster at University of Wyoming

这项奖励是根据2009年《美国复苏和再投资法案》(公法111-5)资助的。授予的资金将用于支持收购NVIDIA Tesla S1070 1.44 GHz GPU计算节点集群，以增强怀俄明大学现有的Linux CPU集群。图形处理单元(GPU)旨在使用多核芯片在并行计算中提供高吞吐量，而图形密集型游戏行业一直是多核芯片的主要市场。NVIDIA最近发布了CUDA(计算统一设备架构)框架GPU编程接口，使得以比在CPU上更高的性价比开发在GPU上运行的并行代码成为可能。PIS将探索由处理能力、速度和吞吐量非常不同的硬件组成的异类集群上科学计算的并行性和可扩展性，开发一套用于地球科学研究的开源、GPU加速的建模和反演代码，并向怀俄明大学地质与地球物理系、计算机科学系和数学系的研究生教授通用GPU计算(GPGPU)。PIS将开发用于地震波传播模拟、全波地震层析成像和流体动力学模拟的GPU代码，用于油藏建模、地下流体流动和溶质运移以及地幔对流。

0930040ChenThis award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). Granted funds will support acquisition of a cluster of NVIDIA Tesla S1070 1.44 GHz GPU computing nodes to augment an existing Linux CPU cluster at the University of Wyoming. Graphic Processing Units (GPUs) are designed to provide high throughput on parallel computations using many-core chips for which the primary market has been the graphic intensive gaming industry. NVIDIA has recently released the CUDA (Compute Unified Device Architecture) framework GPU programming interface making it possible to develop parallel codes to run on GPUs at much higher price/performance than is possible on CPUs. The PIs will explore parallelism and scalability of scientific computing on heterogeneous clusters composed of hardware with very different processing capability, speed and throughput and develop a set of open-source, GPU-accelerated modeling and inversion codes for geoscience research and to teach General-Purpose computation on GPUs (GPGPU) to graduate students at Geology & Geophysics Department, Computer Science Department and Mathematics Department in University of Wyoming. The PIs will develop GPU codes for seismic wave propagation simulations and fullwave seismic tomography and fluid dynamics simulations for oil reservoir modeling, subsurface fluid flow and solute transport and mantle convection.