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Modeling the Impact of Silicon Photonics on Graph Analytics., , , , , , , and . NAS, page 1-11. IEEE Computer Society, (2016)Scalable fine-grained call path tracing., , , , and . ICS, page 63-74. ACM, (2011)Optimizing Distributed Data-Intensive Workflows., , , , and . CLUSTER, page 279-289. IEEE Computer Society, (2018)Generating Performance Models for Irregular Applications., , , , and . IPDPS, page 317-326. IEEE Computer Society, (2017)Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU., , , , , and . CoRR, (2022)HPCVIEW: A Tool for Top-down Analysis of Node Performance., , , and . The Journal of Supercomputing, 23 (1): 81-104 (2002)Deep Learning for Enhancing Fault Tolerant Capabilities of Scientific Workflows., , , and . BigData, page 3905-3914. IEEE, (2018)Towards efficient scheduling of data intensive high energy physics workflows., , , , , and . WORKS@SC, page 3:1-3:9. ACM, (2015)Evaluating On-Node GPU Interconnects for Deep Learning Workloads., , , , and . PMBS@SC, volume 10724 of Lecture Notes in Computer Science, page 3-21. Springer, (2017)A case for application-oblivious energy-efficient MPI runtime., , , , , , and . SC, page 29:1-29:12. ACM, (2015)