AI is a double accelerant, impacting both what and how companies build. The most cautious companies have entered a holding pattern, waiting to see how it all plays out.įor tech-enabled businesses, however, the risk of falling behind is existential. The current hype around AI may give some of us reason to pause - due to the unknown impact to quality, the potential risk of plagiarism and other factors. To move forward, we must first understand and quantify its impact. We’re on a path to repeat ourselves with AI.
#Open source checkbook software how to
How can we make judgments about AI without first agreeing on how to measure productivity? If we learned anything from the remote work experiment, it’s that we floundered without data to inform our decisions - shifting back and forth between office, remote, and hybrid strategies based on dogma and ideology instead of data and measurement. Most of the claims around AI improving productivity today are qualitative - based on surveys and anecdotes, and not on quantitative data. Some have even rejected the idea altogether, arguing that most metrics are flawed or imperfect. The irony, however, is that the engineering community has, for the most part, not been able to agree upon a universal way to measure engineering productivity. One report predicts a tenfold increase in developer productivity by 2030. How much more productive are developers using AI coding tools? Recently, there has been a lot of speculation that AI makes developers 2x, 3x, or even 5x more productive. He holds a Bachelor of Arts in Applied Mathematics from Harvard College and currently resides in Seattle. For more information, please visit / co-founder Geoff Stevens previously worked with the investment team at Volition Capital, a growth equity firm investing in tech-enabled companies. The Office of Science is working to address some of the most pressing challenges of our time. UT-Battelle manages ORNL for DOE’s Office of Science, the single largest supporter of basic research in the physical sciences in the United States.
#Open source checkbook software software
“For UnifyFS, the research results in our IPDPS paper would not have been possible without several years of open-source software development and testing.” “This award is a testament to all the excellent work being done under the Exascale Computing Project to take research prototypes and deliver production-quality software for use on exascale machines,” said Brim. I am very proud of our team and delighted for us to have won the award.” “Even though UnifyFS is cutting-edge software, our team has consistently dedicated significant effort toward making UnifyFS user-friendly and production ready. “I am so happy that the IPDPS conference has chosen to recognize the importance of making HPC research software open source and robust,” said Mohror. This is the first year the conference has offered a Best Open-Source Contribution Award for papers with “open-source tool and dataset artifacts relevant to the parallel and distributed computing community.”
Inset: Senior researcher Kathryn Mohror from Lawrence Livermore National Laboratory.Įvery year, IPDPS selects a few exceptional papers and recognizes one with a Best Paper Award. They are part of the multi-institution team developing UnifyFS.
Sarp Oral, Ross Miller and Mike Brim stand in front of the Frontier supercomputer at ORNL.
This alleviates demand on parallel file systems and reduces I/O bottlenecks that can occur with large-scale applications. The open-source software is a client-level file system that creates a shared namespace for distributed storage resources to allow an application to read and write to node-local storage the same way it would with a parallel file system. The paper presents UnifyFS, the product of a multidisciplinary, multi-institutional software development project that began in 2017. The paper, “UnifyFS: A User-level Shared File System for Unified Access to Distributed Local Storage,” was authored by Michael Brim, Seung-Hwan Lim, Ross Miller, Swen Boehm and Sarp Oral of ORNL with Adam Moody, Cameron Stanavige and Kathryn Mohror of LLNL. A research team from the Department of Energy’s Oak Ridge and Lawrence Livermore national laboratories won the first Best Open-Source Contribution Award for its paper at the 37 th IEEE International Parallel and Distributed Processing Symposium, or IPDPS, which was held in St.
0 kommentar(er)
