1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.AR2023
YFlows: Systematic Dataflow Exploration and Code Generation for Efficient Neural Network Inference using SIMD Architectures on CPUs
Cyrus Zhou, Zack Hassman, Ruize Xu +3
We address the challenges associated with deploying neural networks on CPUs, with a particular focus on minimizing inference time while maintaining accuracy. Our novel approach is…
cs.AR2023★ 1 cited
SONIQ: System-Optimized Noise-Injected Ultra-Low-Precision Quantization with Full-Precision Parity
Cyrus Zhou, Pedro Savarese, Zack Hassman +4
Ultra-low-precision inference can sharply reduce memory and latency but often degrades accuracy and relies on specialized hardware. We present SONIQ, a system-optimized, noise-inje…