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3M-AI: A Multi-task and Multi-core Virtualization Framework for Multi-FPGA AI Systems in the Cloud.

, , , , , , , , , , and . FPGA, page 228. ACM, (2021)

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GraphSAR: a sparsity-aware processing-in-memory architecture for large-scale graph processing on ReRAMs., , , , and . ASP-DAC, page 120-126. ACM, (2019)HyVE: Hybrid Vertex-Edge Memory Hierarchy for Energy-Efficient Graph Processing., , , , and . IEEE Trans. Computers, 68 (8): 1131-1146 (2019)Evaluating Quantized Large Language Models., , , , , , , , and . CoRR, (2024)Sgap: Towards Efficient Sparse Tensor Algebra Compilation for GPU., , , , , , , , and . CoRR, (2022)CogDL: An Extensive Toolkit for Deep Learning on Graphs., , , , , , , , , and 4 other author(s). CoRR, (2021)Sgap: towards efficient sparse tensor algebra compilation for GPU., , , , , , , , and . CCF Trans. High Perform. Comput., 5 (2): 210-227 (June 2023)DF-GAS: a Distributed FPGA-as-a-Service Architecture towards Billion-Scale Graph-based Approximate Nearest Neighbor Search., , , , , , , , , and 1 other author(s). MICRO, page 283-296. ACM, (2023)TorchSparse++: Efficient Training and Inference Framework for Sparse Convolution on GPUs., , , , , , , , and . MICRO, page 225-239. ACM, (2023)3M-AI: A Multi-task and Multi-core Virtualization Framework for Multi-FPGA AI Systems in the Cloud., , , , , , , , , and 1 other author(s). FPGA, page 228. ACM, (2021)NTGAT: A Graph Attention Network Accelerator with Runtime Node Tailoring., , , , , and . ASP-DAC, page 645-650. ACM, (2023)