Search Results for author:
Found 7 papers, 0 papers with code
nl2spec: Interactively Translating Unstructured Natural Language to Temporal Logics with Large Language Models
A rigorous formalization of desired system requirements is indispensable when performing any verification task.
Dynamic Network Adaptation at Inference
Machine learning (ML) inference is a real-time workload that must comply with strict Service Level Objectives (SLOs), including latency and accuracy targets.
RecShard: Statistical Feature-Based Memory Optimization for Industry-Scale Neural Recommendation
EMBs exhibit distinct memory characteristics, providing performance optimization opportunities for intelligent EMB partitioning and placement across a tiered memory hierarchy.
Analysis and Mitigations of Reverse Engineering Attacks on Local Feature Descriptors
This poses a potential risk to user privacy.
RecSSD: Near Data Processing for Solid State Drive Based Recommendation Inference
Neural personalized recommendation models are used across a wide variety of datacenter applications including search, social media, and entertainment.
CPR: Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery
The paper is the first to the extent of our knowledge to perform a data-driven, in-depth analysis of applying partial recovery to recommendation models and identified a trade-off between accuracy and performance.
MeltdownPrime and SpectrePrime: Automatically-Synthesized Attacks Exploiting Invalidation-Based Coherence Protocols
But more importantly, both Prime attacks exploit invalidation-based coherence protocols to achieve the same level of precision as a Flush+Reload attack.
Cryptography and Security Hardware Architecture
