reproducibility

Hi everyone! This is my mid-term blog update for the project MPI Appliance for HPC Research on Chameleon, developed in collaboration with Argonne National Laboratory and the Chameleon Cloud community. This blog follows up on my earlier post, which you can find here.

Mid-project update: Our comprehensive testing framework reveals that the common suspect for RAG non-reproducibility, the FAISS library, is surprisingly deterministic. The true culprits are more subtle: hardware differences and numerical precision. This discovery sharpens our focus on building tools for total environmental control.

Hello! I’m Siva Sathyaseelan D N, a pre-final year B.Tech + M.Tech Engineering student at IIT BHU, Varanasi, India. With a deep-rooted passion for software development and scientific computing. I thrive at the intersection of code and real-world problem-solving.

Introduction Hello there, I’m Michael. In this report, I’ll be sharing my progress as part of the Open Testbed for Reproducible Evaluation of Replicated Systems at the Edges project under the mentorship of Fadhil Kurnia.

Hello! I’m Panji Sri Kuncara Wisma and I want to share my midterm progress on the “Open Testbed for Reproducible Evaluation of Replicated Systems at the Edges” project under the mentorship of Fadhil I.

What is EnvGym? EnvGym is a general multi-agent framework designed to automate the construction of executable environments for reproducing research prototypes from top-tier conferences and journals. While reproducibility has become a growing concern in the research community, the process of setting up environments remains time-consuming, error-prone, and often poorly documented.

Introduction Hello everyone! I am Debangi Ghosh from India, an undergraduate student at the Indian Institute of Technology (IIT) BHU, Varanasi. As part of the StatWrap: Cross-Project Searching and Classification using Local Indexing project, my proposal, under the mentorship of Luke Rasmussen, focuses on developing a full-text search service within the StatWrap user interface.

This project addresses the critical issue of non-determinism in Retrieval-Augmented Generation (RAG) systems. We aim to develop a suite of tools, benchmarks, and best practices to ensure scientific workflows using Large Language Models are reliable, transparent, and reproducible.

PhD student Nicole reflects on how her early experiences with complex scientific workflows shaped her understanding of reproducibility—and why usability is key to making it achievable. This summer, she’s building Jupyter Widgets to reduce friction in reproducible research on the Chameleon cloud platform.