Duration: 1:26:24

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Parallelism abounds in modern hardware—from the datacenter to multi-cores, GPUs, and FPGAs. On the other hand, important algorithms, such as graph algorithms, dynamic programming, and finite-state machine processing involve fine-grained dependencies and do not directly map on to this parallel hardware. Harnessing the parallelism available for these algorithms requires new algorithms, new programming languages, and new runtime systems. This session will present recent advances in this area and will serve as forum for bringing together researchers from diverse disciplines—such as algorithms, programming languages, compilers and runtime, machine-learning, architecture, and systems—into this exciting research area.