Index What is Parallelware Analyzer?– Where to start?– Useful options common to all toolsQuickstart with NAS Parallel Benchmarks Early Access Program is now open! Enter the program to have access to all versions of Parallelware Analyzer and support until the official release. Resources:– NAS Parallel Benchmarks (download C version) – Parallelware Analyzer webpage (link)– Full quickstart […]
News
Appentra selected for Desafía San Francisco in Silicon Valley
We are happy to announce that Appentra has been selected to participate in the Desafía San Francisco Immersion Program, a public initiative sponsored by ICEX and Red.es. We will travel along other nine selected Spanish startups to Silicon Valley in March to attend training sessions, meet investors and know the environment in order to accelerate […]
Parallelware Trainer 1.4 released
We’re glad to announce the release of Parallelware Trainer 1.4 which greatly improves the deployment and user experience in supercomputers by allowing configuration through environment variables. Appentra strives to make parallel programming easier, enabling everyone to make the best use of parallel computing hardware from the multi-cores in a laptop to the fastest supercomputers. With […]
Appentra selected to compete in the Santander X Global Award
Appentra has been selected after a very competitive and thorough evaluation process as a one of the Top 100 participants to compete at the Santander X Global Award. Now, we are part of the Santander X Global Entrepreneurship Community where we’ll have access to world-class resources. It’s time to prepare to pitch our solutions to […]
Appentra BoF at SC19: Quality Assurance and Coding Standards for Parallel Software
Appentra will present a BoF session titled “Quality Assurance and Coding Standards for Parallel Software” at the International Supercomputing Conference 2019 (SC19) in Denver. Date: Thursday, 21st , 12:15pm – 1:15pm Location: 505 BoF Website: https://parallel-code-qa.github.io/sc19-bof/ SC19 BoF info: https://sc19.supercomputing.org/presentation/?id=bof164&sess=sess316 Join us on the mailing list to receive relevant updates and discussions: https://groups.io/g/parallel-code-qa-sc19-bof Parallel programming […]
Appentra at SC19 in Denver
Appentra will once again be participating in the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC19), to be held between 17th and 21th of November. Appentra will take part as an Exhibitor in the Startup Café The Startup Café is the place for emerging companies to introduce their products and services to […]
Appentra announces the Early Access Program for Parallelware Analyzer
Appentra strives to minimize and eventually remove the parallel software development barrier, making parallel computing easier for everyone. Today we announce Parallelware Analyzer, a suite of command-line tools aimed at helping software developers to build better quality parallel software in less time. We are excited to announce that we are also offering developers the opportunity […]
Defects and recommendations for parallelism
Implementing parallel software is hard. On top of all the kinds of bugs that may be present in sequential code, parallel code can also suffer from race conditions. A race condition exists when several threads access the same data at the same time and at least one of them writes to it. Opening the door […]
Fixing defects in parallel code: an OpenMP example
Parallelware Analyzer provides a set of tools covering the most challenging steps of your parallel development workflow. Join the Parallelware Analyzer Early Access Program to get access to the tools for free. In this post, we present the pwcheck tool which provides a static code analyzer to ensure that your code is defect-free and compliant […]
Appentra’s Parallelware Trainer at NERSC Workshop
The National Energy Research Scientific Computing Center (NERSC) will host on October 17th, 2019 a one-day training event on using Appentra’s Parallelware Trainer tool to learn how to use OpenMP and OpenACC directives to develop code for Graphical Processing Units (GPUs). The objective is to improve the learning experience of NERSC users to program the […]