Junqing Sun

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performance better than the GPGPU while the GPGPU shows better time-based performance. I. INTRODUCTION GPGPUs and FPGAs seem to be competing with each other for high performance computing. Many computational science applications are computationally intensive causing huge power consumption. In high performance computing, it is a challenge to keep the power(More)
—Cholesky decomposition has been widely utilized for positive symmetric matrix factorization in solving least square problems. Various parallel accelerators including GPUs and FPGAs have been explored to improve performance. In this paper, Cholesky decomposition is implemented on both FPGAs and GPUs by designing a dedicated architecture for FPGAs and(More)
— This paper is concerned with the problem of controlling plants over communication channels, where the plant is subject to two types of unstructured uncertainty: additive uncertainty and stable coprime factor uncertainty. Necessary lower bounds on the rate of transmission (or channel capacity) C , for robust stabilization, are computed explicitly. In(More)
Higher peak performance on Field Programmable Gate Arrays (FPGAs) than on microprocessors was shown for sparse matrix vector multiplication (SpMxV) accelerator designs. However due to the frequent memory movement in SpMxV, system performance is heavily affected by memory bandwidth and overheads in real applications. In this paper, we introduce an innovative(More)