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.
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).
View or contribute to the experiment packaging and style checklists (appendix A and B) on our GitHub repository here.
Download the report here.
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.
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.
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.
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!
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.
Understanding how to preserve your valuable research on Chameleon Cloud is crucial for research continuity and community contribution. Here's how to extend the lifespan of your resources through smart public sharing
This month, we are excited to announce new updates to the Trovi dashboard, and the launch of the Chameleon User Forums. Additionally, please note our new data policies, as these will take effect soon!
Scientific workflows often fail in unexpected ways, but traditional detection systems require massive amounts of training data. This groundbreaking approach generates just the right data needed to train anomaly detection models, improving accuracy while reducing resource consumption.