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cs.LG2024
Reliable edge machine learning hardware for scientific applications
Tommaso Baldi, Javier Campos, Ben Hawks +15
Extreme data rate scientific experiments create massive amounts of data that require efficient ML edge processing. This leads to unique validation challenges for VLSI implementatio…
cs.LG2024★ 1 cited
Architectural Implications of Neural Network Inference for High Data-Rate, Low-Latency Scientific Applications
Olivia Weng, Alexander Redding, Nhan Tran +2
With more scientific fields relying on neural networks (NNs) to process data incoming at extreme throughputs and latencies, it is crucial to develop NNs with all their parameters s…