3 papers
cs.AR2026
GTAC: A Generative Transformer for Approximate Circuits
Jingxin Wang, Shitong Guo, Wenhui Liang +4
Targeting error-tolerant applications, approximate computing relaxes rigid functional equivalence to significantly improve power, performance, and area. Traditional approximate log…
cs.LG2025
PrefixGPT: Prefix Adder Optimization by a Generative Pre-trained Transformer
Ruogu Ding, Xin Ning, Ulf Schlichtmann +1
Prefix adders are widely used in compute-intensive applications for their high speed. However, designing optimized prefix adders is challenging due to strict design rules and an ex…
cs.LG2025
FAMES: Fast Approximate Multiplier Substitution for Mixed-Precision Quantized DNNs--Down to 2 Bits!
Yi Ren, Ruge Xu, Xinfei Guo +1
A widely-used technique in designing energy-efficient deep neural network (DNN) accelerators is quantization. Recent progress in this direction has reduced the bitwidths used in DN…