Master Thesis in Energy Consumption on Database Management Systems
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Updated
May 18, 2021 - TeX
This topic gathers projects that exemplify or help to provide green computing. Green software is engineered to reduce energy consumption, which considers factors like algorithmic and language efficiency, networking, storage footprint, compute requirements, and so forth. Some projects follow great green software practices that should be highlighted; others help the rest of the world greenify their own code. The projects collected here are a mix of both.
Master Thesis in Energy Consumption on Database Management Systems
Novel blockchain consensus mechanism replacing energy-intensive mining with productive federated learning. Miners collaborate to train AI models, with winners selected through democratic voting.
A repository showcasing my journey through the Green Digital Skills program, focused on understanding and reducing the environmental impact of digital technology.
An ebpf module that exports energy statistics for each process
Monitoring power consumption and calculates CO2 emissions from Kubernetes containers
Research Project by DreamBrook Labs
Jupyter extension to display CPU and GPU power usage and equivalent CO2 emissions
[FGCS] Code and data for the paper "Adaptive green cloud applications: Balancing emissions, revenue, and user experience through approximate computing"
Performance test for trigonometric functions
⚡ Blazing fast Git hooks manager written in Rust. Drop-in replacement for Husky with 27x faster startup. Zero dependencies, parallel execution, and built-in carbon footprint tracking.
An application that measures software energy consumption of user device and computes software carbon intensity for data-driven decision making and software carbon accounting
Distributed Volunteer Computing with IOT
Saas app for physalia
☁️ Cloud GPU platform for AI/ML workloads. Instant access to H100, A100, and RTX GPUs for training and deploying AI models.
A curated collection of research, tools, and best practices for environmentally sustainable AI development and deployment.
Designing energy-aware scheduling and task allocation algorithms for online reinforcement learning in cloud environments (IEEE Transactions on Computational Social Systems).
An attempt to centralized some resources about sustainable programming, green computing and frugal engineering.
Web app for Physalia SaaS