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cs.LG2024
LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation
Mufei Li, Viraj Shitole, Eli Chien +6
Directed acyclic graphs (DAGs) serve as crucial data representations in domains such as hardware synthesis and compiler/program optimization for computing systems. DAG generative m…
cs.LG2023★ 2 cited
Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces
Srinivas Sridharan, Taekyung Heo, Louis Feng +8
Benchmarking and co-design are essential for driving optimizations and innovation around ML models, ML software, and next-generation hardware. Full workload benchmarks, e.g. MLPerf…