Anything you need to get a job in GPGPU and performance-optimized programming
Stream HPC is 10 years old on 1 April 2020. Therefore we offer our one day GPGPU crash course for free that whole month.
Now Corona (and fear for it) spreads, we had to rethink how to celebrate 10 years. So while there were different plans, we simply had to adapt to the market and world dynamics.
We’re collaborating with a few universities on formal verification of GPU code. The project is called ChEOPS: verified Construction of corrEct and Optimised Parallel Software.
We’d like to put the following PhD position to your attention:
Eindhoven University of Technology is seeking two PhD students to work on the ChEOPS project, a collaborative project between the universities of Twente and Eindhoven, funded by the Open Technology Programme of the NWO Applied and Engineering Sciences (TTW) domain.
In the ChEOPS project, research is conducted to make the development and maintenance of software aimed at graphics processing units (GPUs) more insightful and effective in terms of functional correctness and performance. GPUs have an increasingly big impact on industry and academia, due to their great computational capabilities. However, in practice, one usually needs to have expert knowledge on GPU architectures to optimally gain advantage of those capabilities.
Continue reading “GPU-related PHD positions at Eindhoven University and Twente University”
Are you working with Nvidia GPUs in your research and wish Nvidia would support you as they used to 5 years ago? This is now done with hackatons, where you get one full week of support, to get your GPU-code improved and your CPU-code ported. Still you have to do it yourself, so it’s not comparable to services we provide.
To start, get your team on a decision to do this. It takes preparation and a clear formulation of what your goals are.
It’s already April, so some hackatons have already taken place. For 2019, these are left where you can work on any language, from OpenMP to OpenCL and from OpenACC to CUDA. Python + CUDA-libraries is also no problem, as long as the focus is Nvidia.
Continue reading “Academic hackatons for Nvidia GPUs”
GPUs have been our mysterious friends and known enemies for years, as they let us run code in expected and unexpected ways. GPUs have solved problems for many of our customers. GPUs have such a high rate of evolvement, that they’ll remain important for the years to come.
Problem is that programming GPUs is not an easy task. Where do you learn to program GPUs? We found these to be the main groups:
This is far from enough. Add to that, that only a very select group learns the craft at a company. We’d like to change that, and we think now is the time for us to be able to deliver on this.
In January we’ll our internal training program will start with 4 to 8 developers. Focus in on fully understanding recent GPU-architectures, CUDA and OpenCL. It will consist of lectures, workshops, discussions, paper reading and ofcourse coding for one month. The months after that will have guidance, paper presentations, code reviews and time for self-study. The exact form will differ per person.
The current measurable requirements are:
We’re looking for people that fit our culture and we think we can train. This means that the selection is based for a large part on “the spark”. Therefore the application starts with a speed date, and we’re sorry for not finding a better wording for this. This is a 20 minute discussion about what we like and what we don’t. This can be done via phone, Skype or in person, during the evening, in the weekends or during your lunch break.
Read about our company culture. Look at the jobs we have open. These describe the requirements after the training. Then write us a motivational letter: explain us why this is exactly what you want, why you’re capable and why you’re a cultural fit. If you find it hard to write such letter, then just start with answering the list of requirements. It’s a big bonus to share code (Github, Gitlab, zip-file). Send your email to jobs@streamhpc.com
Feeling more senior? We have other jobs:
We’re in the program committee of the 14th IEEE eScience Conference in Amsterdam, organized by the Netherlands eScience Center. It will be held from 29 October to 1 November 2018, and the deadlines for sending the abstracts is Monday 18 June.
The conference brings together leading international researchers and research software engineers from all disciplines to present and discuss how digital technology impacts scientific practice. eScience promotes innovation in collaborative, computationally- or data-intensive research across all disciplines, throughout the research lifecycle.
Continue reading “Call for speakers: IEEE eScience Conference in Amsterdam”
As of this month Stream exists 8 years. 8 full years of helping our customers with fast software.In Chinese numerology 8 is a very lucky number, and we notice that.
Over the years we’ve kept focus on quality and that was a good decision. The only problem is that we don’t have enough time to write on the blog, to organise events or even send the “monthly” newsletter. With over 200 drafts for the blog (subjects that really should be shared), we need extra people to help us out.
Dear developers who are good with C,C++, OpenCL/CUDA and algorithms, please take a look at the following vacancies. I know you are frequenting our blog.
We’re also seeking an all-rounder that supports in daily operations, that includes management, customer contact, team-support, etc.
See below for more details.
We’re looking forward to your application! We accept both remote and Amsterdam-based.
Ever saw a claim on a paper you disagreed with or got triggered by, and then wanted to reproduce the experiment? Good luck finding the code and the data used in the experiments.
When we want to redo experiments of papers, it starts with finding the code and data used. A good start is Github or the homepage of the scientist. Also Gitlab. Bitbucket, SourceForge or the personal homepage of one of the researchers could be a place to look. Emailing the authors is often only an option, if the university homepage mentions such option – we’re not surprised to get no reaction at all. If all that doesn’t work, then implementing the pseudo-code and creating own data might be the only option – not if that will support the claims.
So what if scientific papers had an easy way to connect to digital objects like code and data?
Here the DOI comes in.
Continue reading “DOI: Digital attachments for Scientific Papers”
