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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)GVProf: a value profiler for GPU-based clusters., , , , and . SC, page 89. IEEE/ACM, (2020)Measurement and Analysis of GPU-Accelerated OpenCL Computations on Intel GPUs., , , , and . ProTools@SC, page 26-35. IEEE, (2021)GPA: A GPU Performance Advisor Based on Instruction Sampling., , , and . CGO, page 115-125. IEEE, (2021)Measurement and analysis of GPU-accelerated applications with HPCToolkit., , , , , , , , and . Parallel Comput., (2021)RMBase v2.0: deciphering the map of RNA modifications from epitranscriptome sequencing data., , , , , , , and . Nucleic Acids Res., 46 (Database-Issue): D327-D334 (2018)PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation., , , , , , , , , and 39 other author(s). ASPLOS (2), page 929-947. ACM, (2024)Low overhead and context sensitive profiling of CPU-accelerated applications., , , and . ICS, page 1:1-1:13. ACM, (2022)