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Benchmarking Memory-Centric Computing Systems: Analysis of Real Processing-In-Memory Hardware., , , , , and . IGSC (Workshops), page 1-7. IEEE, (2021)NATSA: A Near-Data Processing Accelerator for Time Series Analysis., , , , , , , and . ICCD, page 120-129. IEEE, (2020)SparseP: Efficient Sparse Matrix Vector Multiplication on Real Processing-In-Memory Architectures., , , , , and . ISVLSI, page 288-291. IEEE, (2022)Sylva: Sparse Embedded Adapters via Hierarchical Approximate Second-Order Information., , , and . ICS, page 485-497. ACM, (2024)DaeMon: Architectural Support for Efficient Data Movement in Fully Disaggregated Systems., , , , , , and . Proc. ACM Meas. Anal. Comput. Syst., 7 (1): 16:1-16:36 (March 2023)An adaptive concurrent priority queue for NUMA architectures., , , , and . CF, page 135-144. ACM, (2019)Minuet: Accelerating 3D Sparse Convolutions on GPUs., , , , , and . EuroSys, page 786-802. ACM, (2024)SMASH: Co-designing Software Compression and Hardware-Accelerated Indexing for Efficient Sparse Matrix Operations., , , , , , , , and . MICRO, page 600-614. ACM, (2019)Combining HTM with RCU to Speed Up Graph Coloring on Multicore Platforms., , and . ISC, volume 10876 of Lecture Notes in Computer Science, page 350-369. Springer, (2018)DaeMon: Architectural Support for Efficient Data Movement in Disaggregated Systems., , , , , , and . CoRR, (2023)