Chameleon Changelog for May 2025

This month, we have new H100 GPU nodes on KVM@TACC! Today, you can launch VM instances with 1 full H100 GPU. This hardware comes with a brand new workflow for reserving VMs. It’s important to note that this reservation workflow will be rolled out to the rest of KVM later in the summer. Additionally, we have refreshed our documentation. Lastly, CHI-in-a-box comes with a new image deploy tool for associate sites.
 

Teaching Cloud Computing with Chameleon: Making Complex Concepts Accessible

How Chameleon Cloud Transforms Computer Science Education Across Europe

Teaching cloud computing effectively requires hands-on experience, but establishing local datacenters or using commercial cloud providers presents significant barriers for students. Chameleon Cloud provides the perfect solution, offering real cloud infrastructure experience without access limitations or costs, enabling comprehensive cloud computing education across European universities.

Leveraging New and Improved Chameleon Images

Less Setup, More Science: Streamlined Images with Built-in Tools and Drivers

What's the secret ingredient that makes our new Chameleon images so much better? From automatic SSH configuration to built-in rclone support, these aren't your ordinary cloud images. Find out what makes them special.

Chameleon Changelog for April 2025

This month, we have new OS images with AMD ROCm and Ubuntu 24 on ARM. Additionally, we have improvements to mounting object store buckets using rclone, a new message-of-the-day, and we’ve fixed the firewall confusion on KVM@TACC.
 

REPETO Releases Report on Challenges of Practical Reproducibility for Systems and HPC Computer Science

Findings from the November 2024 Community Workshop on Practical Reproducibility in HPC

View or contribute to the experiment packaging and style checklists (appendix A and B) on our GitHub repository here.

Download the report here.

We’re excited to announce the publication of the NSF-sponsored REPETO Report on Challenges of Practical Reproducibility for Systems and HPC Computer Science, a culmination of our Community Workshop on Practical Reproducibility in HPC, held in November 2024 in Atlanta, GA (reproduciblehpc.org).

Fair-CO2: Fair Attribution for Cloud Carbon Emissions

Understanding and accurately distributing responsibility for carbon emissions in cloud computing

Leo Han, a second-year Ph.D. student at Cornell Tech, conducted pioneering research on the fair attribution of cloud carbon emissions, resulting in the development of Fair-CO2. Enabled by the unique bare-metal capabilities and flexible environment of Chameleon Cloud, this work tackles the critical issue of accurately distributing responsibility for carbon emissions in cloud computing. This research underscores the potential of adaptable testbeds like Chameleon in advancing sustainability in technology.

Faster Multimodal AI, Lower GPU Costs

HiRED: Cutting Inference Costs for Vision-Language Models Through Intelligent Token Selection

High-resolution Vision-Language Models (VLMs) offer impressive accuracy but come with significant computational costs—processing thousands of tokens per image can consume 5GB of GPU memory and add 15 seconds of latency. The HiRED (High-Resolution Early Dropping) framework addresses this challenge by intelligently selecting only the most informative visual tokens based on attention patterns. By keeping just 20% of tokens, researchers achieved a 4.7× throughput increase and 78% latency reduction while maintaining accuracy across vision tasks. This research, conducted on Chameleon's infrastructure using RTX 6000 and A100 GPUs, demonstrates how thoughtful optimization can make advanced AI more accessible and affordable.

Importing GitHub Repositories to Trovi: A Step-by-Step Guide

Streamline Your Research Workflow with Trovi's New GitHub Integration

Learn how to leverage Trovi's new GitHub integration to easily create and update reproducible research artifacts. This step-by-step guide shows you how to configure your GitHub repository with RO-crate metadata and import it directly into Trovi, enabling better collaboration and adherence to FAIR principles for your experiments.

Chameleon Changelog for March 2025

This month, we have reminders for KVM@TACC and CHI@Edge outages later this month. Additionally, we have version 1.1 of python-chi, and improvements to reservations!
 

EditLord: Learning Code Transformation Rules for Code Editing

Making code edits more effective, robust, and transparent through explicit transformation rules

In this interview, Weichen Li, a PhD student from the University of Chicago discusses research on improving code editing through explicit transformation rules. EditLord breaks down the code editing process into clear, step-by-step transformations, significantly enhancing editing performance, robustness, and functional correctness compared to existing methods.