Reports

Introduction Motivation The growing popularity of Deep Neural Networks has resulted in a substantial increase in demand for Graphics Processing Units (GPUs). GPUs are crucial for conducting matrix computations in DNN training and inference.

Mid-Term Evaluation Update Hello! I’m Nick, a GSoC contributor for the Proactive Data Containers (PDC) Project. Over the past few weeks I’ve worked on verifying the functionality of the Python API for the PDC project and ensuring the smooth onboarding for new users of the data containers.

Hello again! This is Luiza, a GSoC contributor for the LabOp Project. My task is to build bridges between programming languages for Biotechnology Laboratory automation. When talking about life sciences, reproducibility is a issue amongst most research centers.

As part of the Polyphy Project, my proposal was aimed at improving various aspects of the project, including CI/CD workflows, encapsulation, and security. Under the mentorship of Oskar Elek, I have made significant progress in the following areas:

Introduction Hello again! This is Jack, a GSoC contributor for the OpenROAD Project. My task is to update and optimise the documentation to encourage user adoption and engagement. For open-source repo maintainers, readthedocs is a godsend.

Hello there! I’m Jonathan Edwin, all the way from the beautiful archipelago of Indonesia. This year, I got the exciting chance to jump on board the 2023 Summer of Reproducibility initiative.

As part of the Reproducible Analysis & Models for Predicting Genomics Workflow Execution Time my proposal under the mentorship of In Kee Kim, Martin Putra and collaborator Charis Christopher Hulu (another OSRE fellow) aims to analyze large-scale sequencing datasets in order to gain insights on how ‘input quality’ affects genomic workflows’ execution times.

As part of Micro Architecture Santa Cruz (MASC) my proposal under the mentorship of Jose Renau aims to develop syntax highlighting and a vertical alignment tool for Pyrope. Pyrope is a modern hardware description language under development by MASC.

This project’s goal is to novel data abstraction for managing science data in an object-oriented manner. PDC’s will provide efficient strategies for moving data in deep storage hierarchies and techniques for transforming and reorganizing data based on application requirements. By developing an Python API and command line tools, these objects will be able to be used with ease regardless of the situation.

This project aims to design a system that allows researchers to conveniently record and compare the environmental information, such as CPU utilization, of different iterations and versions of code during an experiment.