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Scalability Limitations of Processing-in-Memory using Real System Evaluations.

, , , , , , , , , , and . SIGMETRICS/Performance (Abstracts), page 63-64. ACM, (2024)

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Scalability Limitations of Processing-in-Memory using Real System Evaluations., , , , , , , , , and 1 other author(s). SIGMETRICS/Performance (Abstracts), page 63-64. ACM, (2024)Accelerating Polynomial Multiplication for Homomorphic Encryption on GPUs., , , , , , , , and . SEED, page 61-72. IEEE, (2022)MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training., , , , , , , , and . ASPLOS (2), page 683-698. ACM, (2024)JAXED: Reverse Engineering DNN Architectures Leveraging JIT GEMM Libraries., , , and . SEED, page 189-202. IEEE, (2021)NeuraChip: Accelerating GNN Computations with a Hash-based Decoupled Spatial Accelerator., , , , , , , and . ISCA, page 946-960. IEEE, (2024)SMASH: Sparse Matrix Atomic Scratchpad Hashing.. CoRR, (2021)GME: GPU-based Microarchitectural Extensions to Accelerate Homomorphic Encryption., , , , , , , , , and 2 other author(s). MICRO, page 670-684. ACM, (2023)GNNMark: A Benchmark Suite to Characterize Graph Neural Network Training on GPUs., , , , , , , , , and 1 other author(s). ISPASS, page 13-23. IEEE, (2021)Accelerating Finite Field Arithmetic for Homomorphic Encryption on GPUs., , , , , , , , and . IEEE Micro, 43 (5): 55-63 (September 2023)