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GPU computing in discrete optimization. Part I: Introduction to the GPU [PDF]
EURO Journal on Transportation and Logistics, 2013 In many cases there is still a large gap between the performance of current optimization technology and the requirements of real world applications. As in the past, performance will improve through a combination of more powerful solution methods and a general performance increase of computers. These factors are not independent.
André Brodtkorb +2 more
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GPUs and the Future of Parallel Computing
IEEE Micro, 2011This article discusses the capabilities of state-of-the art GPU-based high-throughput computing systems and considers the challenges to scaling single-chip parallel-computing systems, highlighting high-impact areas that the computing research community can address.
Stephen W. Keckler +4 more
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Fault Table Computation on GPUs
Journal of Electronic Testing, 2010In this paper, we explore the implementation of fault table generation on a Graphics Processing Unit (GPU). A fault table is essential for fault diagnosis and fault detection in VLSI testing and debug. Generating a fault table requires extensive fault simulation, with no fault dropping, and is extremely expensive from a computational standpoint.
Kanupriya Gulati, Sunil P. Khatri
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Extending OpenSHMEM for GPU Computing
2013 IEEE 27th International Symposium on Parallel and Distributed Processing, 2013Graphics Processing Units (GPUs) are becoming an integral part of modern supercomputer architectures due to their high compute density and performance per watt. In order to maximize utilization, it is imperative that applications running on these clusters have low synchronization and communication overheads.
Sreeram Potluri +4 more
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CPUs, GPUs, and Hybrid Computing
IEEE Micro, 2011This introduction to the special issue discusses advances and challenges in the field of hybrid CPU/GPU computing.
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Throughput Computing on Future GPUs
2010The focus on throughput and large data volumes separates Information Retrieval (IR) from scientific computing, since for IR it is critical to process large amounts of data efficiently, a task which the GPU currently does not excel at. Only recently has the IR community begun to explore the possibilities, and an implementation of a search engine for the
Rune J. Hovland, Anne C. Elster
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Integral image computation on GPU
10th International Multi-Conferences on Systems, Signals & Devices 2013 (SSD13), 2013In this paper we present an integral image algorithm that can run in real-time on a Graphics Processing Unit (GPU). Our system exploits the parallelisms in computation via the NVIDA CUDA programming model, which is a software platform for solving non-graphics problems in a massively parallel high performance fashion.
Marwa Chouchene +3 more
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GPU Computing for Atmospheric Modeling
Computing in Science & Engineering, 2010Much success has been achieved using GPUs to accelerate existing applications that are highly data parallel, or that are dominated by small, intense computational kernels. What are the prospects for porting existing large scientific models that do not fit this mold?
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2009 15th International Conference on Parallel and Distributed Systems, 2009
Counting sort is a simple, stable and efficient sort algorithm with linear running time, which is a fundamental building block for many applications. This paper depicts the design issues of a data parallel implementation of the count sort algorithm on a commodity multiprocessor GPU using the Compute Unified Device Architecture (CUDA) platform, both ...
Weidong Sun, Zongmin Ma 0001
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Counting sort is a simple, stable and efficient sort algorithm with linear running time, which is a fundamental building block for many applications. This paper depicts the design issues of a data parallel implementation of the count sort algorithm on a commodity multiprocessor GPU using the Compute Unified Device Architecture (CUDA) platform, both ...
Weidong Sun, Zongmin Ma 0001
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GPU Computing: The Future of Computing
Proceedings of the West Virginia Academy of Science, 2018PARKER ANTHONY, Department of Computer Science, Mathematics, and Engineering, Shepherd University, Shepherdstown, WV, 25443.Computing requirements have grown over the last few years, bringing with it the benefits of complex computing. However, this had led to a bottleneck within the system.
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