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Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators
The algorithms and accelerator cost models are connected via a novel mapping abstraction that captures the map space of spatial accelerators which can be systematically pruned based on constraints from the hardware, workload, and mapper.
Smart-PGSim: Using Neural Network to Accelerate AC-OPF Power Grid Simulation
In this paper, we develop a neural network approach to the problem of accelerating the current optimal power flow (AC-OPF) by generating an intelligent initial solution.
Runtime Concurrency Control and Operation Scheduling for High Performance Neural Network Training
These frameworks employ a dataflow model where the NN training is modeled as a directed graph composed of a set of nodes.
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