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EDD: Efficient Differentiable DNN Architecture and Implementation Co-search for Embedded AI Solutions.

, , , , , , , and . DAC, page 1-6. IEEE, (2020)

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Efficient and Scalable Workflows for Genomic Analyses., , , , , , and . DIDC@HPDC, page 27-36. ACM, (2016)Critical issues regarding HPS, a high performance microarchitecture., , , and . MICRO, page 109-116. ACM/IEEE, (1985)HPS, a new microarchitecture: rationale and introduction., , and . MICRO, page 103-108. ACM/IEEE, (1985)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)Using Profile Information to Assist Advaced Compiler Optimization and Scheduling., , , , , , , , , and . LCPC, volume 757 of Lecture Notes in Computer Science, page 31-48. Springer, (1992)The superblock: An effective technique for VLIW and superscalar compilation., , , , , , , , , and 2 other author(s). J. Supercomput., 7 (1-2): 229-248 (1993)Adaptive Cache Bypass and Insertion for Many-core Accelerators., , , , , , and . MES, page 1-8. ACM, (2014)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)PIGEON: Optimizing CUDA Code Generator for End-to-End Training and Inference of Relational Graph Neural Networks., , , , , , and . CoRR, (2023)