1 citations · 1 across the 4 of their papers we have counts for
4 papers
Energy-Efficient Multimodal Inference Serving with Tri-serve
Ziyang Jia, Sara Rashidi Golrouye, Laxmi Bhuyan +5
Multimodal model inference creates substantial energy demand with growing performance requirements. Within GPUs, power is autonomously managed by an on-board power management unit…
Guac: Energy-Aware and SSA-Based Generation of Coarse-Grained Merged Accelerators from LLVM-IR
Iulian Brumar, Rodrigo Rocha, Alex Bernat +3
Designing accelerators for resource- and power-constrained applications is a daunting task. High-level Synthesis (HLS) addresses these constraints through resource sharing, an opti…
ArchGym: An Open-Source Gymnasium for Machine Learning Assisted Architecture Design
Srivatsan Krishnan, Amir Yazdanbaksh, Shvetank Prakash +8
Machine learning is a prevalent approach to tame the complexity of design space exploration for domain-specific architectures. Using ML for design space exploration poses challenge…
PerfSAGE: Generalized Inference Performance Predictor for Arbitrary Deep Learning Models on Edge Devices
Yuji Chai, Devashree Tripathy, Chuteng Zhou +6
The ability to accurately predict deep neural network (DNN) inference performance metrics, such as latency, power, and memory footprint, for an arbitrary DNN on a target hardware p…