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A tool for top-down performance analysis of GPU-accelerated applications., , and . PPoPP, page 415-416. ACM, (2020)Tools for top-down performance analysis of GPU-accelerated applications., , and . ICS, page 26:1-26:12. ACM, (2020)Centimani: Enabling Fast AI Accelerator Selection for DNN Training with a Novel Performance Predictor., , , , , , , and . USENIX ATC, page 1203-1221. USENIX Association, (2024)ChIPBase v2.0: decoding transcriptional regulatory networks of non-coding RNAs and protein-coding genes from ChIP-seq data., , , , , , and . Nucleic Acids Res., 45 (Database-Issue): D43-D50 (2017)Quadboost: A Scalable Concurrent Quadtree., , and . CoRR, (2016)ValueExpert: exploring value patterns in GPU-accelerated applications., , , , and . ASPLOS, page 171-185. ACM, (2022)Hardware-Aware Compression with Random Operation Access Specific Tile (ROAST) Hashing., , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 7732-7749. PMLR, (2023)A performance analysis framework for exploiting GPU microarchitectural capability., , , , and . ICS, page 15:1-15:10. ACM, (2017)Outcomes of OpenMP Hackathon: OpenMP Application Experiences with the Offloading Model (Part II)., , , , , , , , , and 15 other author(s). IWOMP, volume 12870 of Lecture Notes in Computer Science, page 81-95. Springer, (2021)Low overhead and context sensitive profiling of CPU-accelerated applications., , , and . ICS, page 1:1-1:13. ACM, (2022)