ACM

TEMpesT: Testing Empirically for Memory Transistency
Research

TEMpesT: Testing Empirically for Memory Transistency

Abstract TEMpesT is a novel empirical testing methodology designed to rigorously verify memory transistency behaviors in modern CPU implementations, specifically targeting the complexities of the RISC-V Weak Memory Ordering (RVWMO) model. The system
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A Survey of Machine Learning Approaches in Logic Synthesis
Research

A Survey of Machine Learning Approaches in Logic Synthesis

Abstract This survey provides a comprehensive review of the rapidly evolving landscape concerning the integration of Machine Learning (ML) techniques into classical Logic Synthesis workflows. It systematically categorizes various ML applications—ranging from
By Admin 2 min read