4 papers · 1 filter
FORGE: Procedural Weight Generation for Sparse MoE Inference
Chanyoung Moon, Travis Pence, Daisuke Yamada +4
We introduce FORGE (Fast On-chip Rotor Generation for Experts), a procedural weight generation system for Sparse Mixture-of-Experts (MoE) inference. Rather than storing and loading…
Beyond Static Policies: Dynamic Selection Among Modern Microarchitectural Policies
Yanxin Zhang, Ian McDougall, Junnan Li +3
Modern processors gain performance from interacting policies: prefetchers, predictors, replacement rules, and schedulers. These policies are often evaluated one at a time, yet a po…
Beyond Static Policies: Exploring Dynamic Policy Selection for Single-Thread Performance Optimization
Yanxin Zhang, Ian McDougall, Junnan Li +3
For over a decade, processor design has focused on implementing sophisticated policies for various components of the out-of-order pipeline, including cache replacement and prefetch…
NeuroScalar: A Deep Learning Framework for Fast, Accurate, and In-the-Wild Cycle-Level Performance Prediction
Shayne Wadle, Yanxin Zhang, Vikas Singh +1
The evaluation of new microprocessor designs is constrained by slow, cycle-accurate simulators that rely on unrepresentative benchmark traces. This paper introduces a novel deep le…