Execution Time

Execution time, the duration a program or task takes to complete, is a critical performance metric across diverse computing domains. Current research focuses on optimizing execution time through various strategies, including the development of novel algorithms like reinforcement learning to improve compiler optimization phases and the application of neural networks to predict and optimize execution timing in time-series forecasting and resource-constrained systems such as embedded devices. These advancements aim to reduce energy consumption, improve efficiency, and enhance security by mitigating vulnerabilities like prompt injection attacks, ultimately impacting the performance and resource utilization of various applications from embedded systems to large-scale data processing.

Papers

March 6, 2024

Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks
Dario Pasquini, Martin Strohmeier, Carmela Troncoso
LeArning Abstract Prompt Injection Attack Execution Time

October 9, 2023

Deep Optimal Timing Strategies for Time Series
Chen Pan, Fan Zhou, Xuanwei Hu, Xinxin Zhu, Wenxin Ning, Zi Zhuang, Siqiao Xue, James Zhang, Yunhua Hu
Time Series Probabilistic Time Series Forecasting Optimal Timing Probabilistic Forecasting Execution Time

February 22, 2023

Multi-objective optimization of energy consumption and execution time in a single level cache memory for embedded systems
Josefa Díaz Álvarez, José L. Risco-Martín, J. Manuel Colmenar
System Description Multi Objective Optimization Energy Consumption Multi Objective Evolutionary Algorithm Cache Context Caching Strategy Execution Time Cache Memory

July 27, 2022

POSET-RL: Phase ordering for Optimizing Size and Execution Time using Reinforcement Learning
Shalini Jain, Yashas Andaluri, S. VenkataKeerthy, Ramakrishna Upadrasta
Reinforcement Learning Order Matter Size Matter Civil Engineering Phase Modern Compiler Sequential Optimization Code Optimization Level Virtual Machine Execution Time

Execution Time

Papers

Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks

Deep Optimal Timing Strategies for Time Series

Multi-objective optimization of energy consumption and execution time in a single level cache memory for embedded systems

POSET-RL: Phase ordering for Optimizing Size and Execution Time using Reinforcement Learning