Hacker News with Generative AI: Resource Management

JavaScript's New Superpower: Explicit Resource Management (v8.dev)
The Explicit Resource Management proposal introduces a deterministic approach to explicitly manage the lifecycle of resources like file handles, network connections, and more.

JavaScript, Programming Languages, Software Development, Resource Management

329 points by olalonde 7 days ago | 232 comments

Decent living standards for 8.5B would require 30% of current resource use (sciencedirect.com)
Some narratives in international development hold that ending poverty and achieving good lives for all will require every country to reach the levels of GDP per capita that currently characterise high-income countries.

Sustainable Development, Resource Management, Economics, Inequality

51 points by isomorph 60 days ago | 26 comments

Autothrottle: Resource Management for SLO-Targeted Microservices (usenix.org)
Achieving resource efficiency while preserving end-user experience is non-trivial for cloud application operators.

Cloud Computing, Microservices, Resource Management, Software Engineering, System Optimization

22 points by mlerner 110 days ago | 1 comments

Linux 6.14 Resource Control to Allow Total Memory Bandwidth Monitoring (phoronix.com)
The x86/cache updates for the in-development Linux 6.14 kernel are extending the Resource Control "resctrl" code for Intel Resource Director Technology / AMD Platform Quality of Service to have the capability of total memory bandwidth monitoring.

Linux, Operating Systems, Performance, Resource Management, Hardware

3 points by LinuxBender 122 days ago | 0 comments

Welcome to M.U.L.E (muttoo.on.ca)
M.U.L.E. is a game of exploration and resource development on another planet.

Gaming, Space Exploration, Resource Management

6 points by debo_ 179 days ago | 0 comments

Fair: A Go library for serving resources fairly (github.com/satmihir)
FAIR is a Go library designed to ensure fairness in the resource-constrained environments. It helps distribute the limited resources (e.g., database/blob storage throughput, job execution resources etc.) evenly across multiple clients during the time of shortage, preventing over-allocation and starvation based on client behavior.