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:
- Universities
- Research centers
- GPU vendors (AMD, Nvidia, Intel, Qualcomm, ARM)
- Self-study
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 hard side
The current measurable requirements are:
- EU citizen or already having a working permit
- Great at C/C++
- High interest in algorithmic optimisations
- Any performance improvement focus (i.e. Assembly, clean code) is a plus
- Any GPU experience (i.e. OpenGL, DirectX, self-study) is a plus
- High interest in performance
- Willing to move to Amsterdam
- Willing to work for Stream HPC for at least 2 years
The soft side
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.
How to apply
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
Other jobs
Feeling more senior? We have other jobs:
Our managing director, 
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.
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 CUDA kept having a dominance over OpenCL, AMD introduced HIP – a programming language that closely resembles CUDA. Now it doesn’t take months to port code to AMD hardware, but more and more CUDA-software converts to HIP without problems. The real large and complex code-bases only take a few weeks max, where we found that solved problems also made the CUDA-code run faster.
It takes quite some effort to program FPGAs using VHDL or Verilog. Since several years Intel/Altera has OpenCL-drivers, with the goal to reduce this effort. OpenCL-on-FPGAs reduced the required effort to a quarter of the time, while also making it easier to alter the specifications during the project. Exactly the latter was very beneficiary when creating the demo, as the to-be-solved problem was vaguely defined. The goal was to make a video look like a cartoon using image filters. We soon found out that “cartoonized” is a vague description, and it took several iterations to get the right balance between blur, color-reduction and edge-detection. 
A month ago IWOCL (OpenCL workshop) and DHPCC++ (C++ for GPUs) took place. Meanwhile many slides and posters have been 
Most of our projects are around performance optimisation, but we’re cleaning up bugs too. This is because you can only speed up software when certain types of bugs are cleared out. A few months ago, we got a different type of request. If we could solve bugs in MESA 3D that appear in games.
In the perfect world all software is fast, giving us time to do actual work. Unfortunately we live in an unperfect world, and we have to spend extra time controlling our anger as the software keeps us waiting.
