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A tool for top-down performance analysis of GPU-accelerated applications., , и . PPoPP, стр. 415-416. ACM, (2020)Tools for top-down performance analysis of GPU-accelerated applications., , и . ICS, стр. 26:1-26:12. ACM, (2020)Centimani: Enabling Fast AI Accelerator Selection for DNN Training with a Novel Performance Predictor., , , , , , , и . USENIX ATC, стр. 1203-1221. USENIX Association, (2024)Low overhead and context sensitive profiling of CPU-accelerated applications., , , и . ICS, стр. 1:1-1:13. ACM, (2022)Understanding the GPU Microarchitecture to Achieve Bare-Metal Performance Tuning., , , , , и . PPoPP, стр. 31-43. ACM, (2017)A Tool for Performance Analysis of GPU-Accelerated Applications., и . CGO, стр. 282. IEEE, (2019)Multi-Classes Feature Engineering with Sliding Window for Purchase Prediction in Mobile Commerce., , , и . ICDM Workshops, стр. 1048-1054. IEEE Computer Society, (2015)RMBase v2.0: deciphering the map of RNA modifications from epitranscriptome sequencing data., , , , , , , и . Nucleic Acids Res., 46 (Database-Issue): D327-D334 (2018)Measurement and analysis of GPU-accelerated applications with HPCToolkit., , , , , , , , и . Parallel Comput., (2021)GPA: A GPU Performance Advisor Based on Instruction Sampling., , , и . CGO, стр. 115-125. IEEE, (2021)