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Programming Massively Parallel Processors: A Hands-on Approach (Applications of GPU Computing Series)

, and . Morgan Kaufmann, 1 edition, (Feb 5, 2010)

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Checkpoint Repair for High-Performance Out-of-Order Execution Machines., and . IEEE Trans. Computers, 36 (12): 1496-1514 (1987)Advanced MRI reconstruction toolbox with accelerating on GPU., , , , , , , , and . Parallel Processing for Imaging Applications, volume 7872 of SPIE Proceedings, page 78720Q. SPIE, (2011)Adaptive Cache Bypass and Insertion for Many-core Accelerators., , , , , , and . MES, page 1-8. ACM, (2014)An efficient GPU implementation and scaling for higher-order 3D stencils., , , and . Inf. Sci., (2022)Heterogeneous Computing Meets Near-Memory Acceleration and High-Level Synthesis in the Post-Moore Era., , , and . IEEE Micro, 37 (4): 10-18 (2017)FCUDA-HB: Hierarchical and Scalable Bus Architecture Generation on FPGAs With the FCUDA Flow., , , , , , , , and . IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 35 (12): 2032-2045 (2016)CODAG: Characterizing and Optimizing Decompression Algorithms for GPUs., , , , , , , , , and 3 other author(s). CoRR, (2023)PyTorch-Direct: Enabling GPU Centric Data Access for Very Large Graph Neural Network Training with Irregular Accesses., , , , , , , and . CoRR, (2021)Bottom-Up and Top-Down Context-Sensitive Summary-Based Pointer Analysis., , and . SAS, volume 3148 of Lecture Notes in Computer Science, page 165-180. Springer, (2004)Characterizing the impact of predicated execution on branch prediction., , , , , and . MICRO, page 217-227. ACM / IEEE Computer Society, (1994)