General articles

Join us at the Dutch eScience Symposium 2019 in Amsterdam

Soon there will be another Dutch eScience Symposium 2019 in Amsterdam. We thought it might be a good place to meet and listen to e-science talks. Stream HPC in the end is just making scientific software, so we’re here at the right place. The eScience Center is a government institute that aims to advance eScience in the Netherlands.

Interested? Read on!

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We accelerated the OpenCL backend of pyPaSWAS sequence aligner

Last year we accelerated the OpenCL-code in PaSWAS, which is open source software to do DNA/RNA/protein sequence alignment and trimming. It has users world-wide in universities, research groups and industry.

Below you’ll find the benchmark results of our acceleration work. You can also test out yourself, as the code is public. In the readme-file you can learn more about the idea of the software. Lots of background information is described in these two papers:

We chose PaSWAS because we really like bio-informatics and computational chemistry – the science is interesting, the problems are complex and the potential GPU-speedup is real. Other examples of such software we worked on are GROMACS and TeraChem.

Continue reading “We accelerated the OpenCL backend of pyPaSWAS sequence aligner”

Do you have our GPU DNA?

This is the first question to warm up. Python-programmers are often users of GPU-libraries, not the builders of those libraries.

In January 2019 I gave a talk about culture in the company, which I wanted to share with you. It was intended to trigger discussions on what environment fits somebody, and examples were given on other companies. The nice part was that it became more clear that the culture of a company like CodePlay was very alike, except they are working on different things (compilers). Same for departments of larger companies we work with or know well.

Important: all answered are based on what my colleagues answered. So most of us are cat-people, but I wouldn’t say that defines a GPU-developer. I hope it still gives you an understanding of our perspective on what defines a GPU-dev in just a few minutes, while it also gives you more than enough matter to think about.

Continue reading “Do you have our GPU DNA?”

Stream Team at ISC

This year we’ll be with 4 people at ISC: Vincent, Adel, Anna and Istvan. You can find us at booth G-812, next to Red Hat.

Booth G-812 is manned&womened by Stream HPC

While we got known in the HPC-world for our expertise on OpenCL, we now have many years of experience in CUDA and OpenMP. To get there, we’ve focused a lot on how to improve code quality of existing software, to reduce bugs and increase speedup-potential. Our main expertise remains full control over algorithms in software – the same data simply processed faster.

Why do we have a booth?

We’ll be mostly talking to (new) customers for development of high performance software for the big machines. Also we’ll have a list of our open job positions with us, and we can do the first introductory interview on the spot.

Our slogan for this year is:

There are a lot of supercomputers. Somebody has to program its software

We’ll be sharing our week on Twitter, so you can also see what we find: posters about HPC-programming on CPU and GPU, booths that have nice demos or interesting talks and ofcourse the surprises.

Let’s meet!

If you don’t have an appointment yet, but would like to chat with us, please contact us or drop by at our booth. As we’re with four people, we have high flexibility.

GPU-related PHD positions at Eindhoven University and Twente University

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.

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Academic hackatons for Nvidia GPUs

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.

When and where?

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.

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IWOCL 2019

On Monday May 13, 2019 at 09:30 the latest edition of IWOCL starts, not taking into account any pre-events that might be spontaneously organized. This is the biggest OpenCL-focused event that discusses everything that would make any GPGPU-programmer, DSP-programmer and FPGA-programmer enthusiastic.

What’s new since last year, is that it’s actually also more interesting place for CUDA-developers who like to learn and discuss new GPU-programming techniques. This is because Nvidia’s GTC has moved more to AI, where it used to be mostly GPGPU for years.

Since it’s now the last week of the early-bird pricing, it’s a good time to make you think about buying your ticket and book the trip.

Continue reading “IWOCL 2019”

Question: do we work with CUDA?

Answer: Yes, actually a lot!

The company was built on OpenCL and we are still work with the language a lot – from embedded GPUs and FPGAs to high-end GPUs. Like OpenCL unjustly isn’t associated with clusters full of professional GPUs, we were not associated with CUDA. I can tell many of our customers have found us to build high performance software in CUDA.

Breaking with the past is not easy due to associations that seem to stick. With the name change from StreamComputing to Stream HPC some years ago, we wanted to enforce that break with being “the OpenCL company”. For some time we were much more pragmatic in solving the problems of our customers, which resulted in making software in MPI and CUDA – sometimes an unexpected direction as the customer initially chose OpenCL.

We also started hiring people who only knew CUDA (but expect them to learn OpenCL), as the right algorithm and the right processor is more important. Internships with CUDA, large CUDA-projects, seeking better relations with Nvidia and such – all have been going on for years. And we like it as much as we like OpenCL – both have unique advantages.

So if you have questions about CUDA, don’t be afraid that you hurt us – we’re happy to help you get fast software.

The 12 latest Twitter Poll Results of 2018

Via our Twitter channel we have various polls. Not always have we shared the full background of these polls, so we’ve taken the polls of the past half year and put them here. The first half of the year there were no polls, in case you wanted to know.

As inclusive polls are not focused (and thus difficult to answer), most polls are incomplete by design. Still insights can be given. Or comments given.

Below’s polls have given us insight and we hope they give you insights too how our industry is developing. It’s sorted on date from oldest first.

It was very interesting that the percentage of votes per choice did not change much after 30 votes. Even when it was retweeted by a large account, opinions had the same distribution.

Is HIP (a clone of CUDA) an option?

Continue reading “The 12 latest Twitter Poll Results of 2018”

We don’t work for the war-industry

Last week we emphasized that we don’t work for the war-industry. We did talk to a national army some years ago, but even though the project never started, we would have probably said no. Recently we got a new request, got uncomfortable and did not send a quote for the training.

This is because we like to think about the next 100 years, and investment in weapons is not something that would solve things for the long term.

To those, who liked the tweet or wanted to, thank you for your support to show us we’re not standing alone here. Continue reading “We don’t work for the war-industry”

OpenCL Basics: Running multiple kernels in OpenCL

This series “Basic concepts” is based on GPGPU-questions we get via email more than once, or when the question is not clearly explained in the books. For one it is obvious, for the other just what they’re missing.

They say that learning a new technique is best done by playing around with working code and then try to combine it. The idea is that when you have Stackoverflowed and Githubed code together, you’ve created so many bugs by design that you’ll learn a lot if you make it work. When applying this to OpenCL, you quickly get to a situation that you want to run one.cl file and then another.cl file. Almost all beginner’s material discuss a single OpenCL-file, so how to do this elegantly?

Continue reading “OpenCL Basics: Running multiple kernels in OpenCL”

Start your GPU-career here

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:

    What does it mean to work at Stream HPC?

    High performance computing on many-core environments and low-level optimisations are very important concepts in large scientific projects nowadays. Stream HPC is one of the market’s more prominent clubs and is substantially expanding. As we often get asked how it is to work at the company, we’d like to give you a little peak into our kitchen.

    Stream HPC’s DNA

    To understand our DNA, you’d need to know how the company got started. In 2010 the company was born from the deep boredom that was born from within the corporate IT workspace. Stream’s founder Vincent Hindriksen had to maintain a piece of software that was often failing to process the daily reports. After documenting the internals and algorithms of the code by interviewing the key people and some reverse engineering, it was a lot easier to create effective solutions for the bugs within the software. After fixing a handful of bugs, there was simply a lot less to do except reading books and playing online games.

    To avoid becoming a master in Sudoku, he spent the following three weeks in rewriting all the code, using the freshly produced documentation. 2.5 hours needed to process the data was reduced to 19 seconds – yes, the kick for performance optimisation was already there. For some reason it took well over 6 months to port the proof-of-concept, which was simply unbearable as somebody had to make sure the old code was maintained for 40 hours a week.

    The reason to start the company was simple: to make intelligent use of time and provide software that is engineered for performance and maintainability. Lots of exciting projects for fantastic clients followed in the next 8 years that allowed us to broaden our expertise and build up confidence. GPUs were there at just the right time – without GPUs it would have probably been performance engineering on CPUs.

    Continue reading “What does it mean to work at Stream HPC?”

    Meet Vincent in Bay Area between 11 and 16 August

    Our managing director, Vincent Hindriksen, is in San Francisco’s Bay Area from Saturday 11th up to Thursday 16th of August 2018. He’ll be visiting existing customers, but there is time left.

    Current schedule (excluding several unconfirmed meetings):

    • Saturday: social meetups
    • Monday: full
    • Tuesday: all day good availability,
    • Wednesday: all day good availability
    • Thursday: morning good availability

    Do you want to learn more about GPUs and how we can help you get there? Get in touch via our contact-page, and tell us address and time when you want to meet.

    If you seek a job in GPUs, also get in contact! Stream HPC is growing quickly now, and a good moment to onboard and still make a difference. For job-talks also the evenings are available.

    Help us find our future COO

    Is this a motto that goes with your personality? Then we want to talk with you.
    After 8 years the time has come that we have continuous growth for almost 2 years, instead of dealing with the usual peaks and lows of consultancy. I’d like to get your help to find our future COO to help streamline this growth.
    You might have seen that there are hardly any new blog posts – now you know why. By helping us find that special person, there can be put more time of writing new blog posts again.
    If you know the perfect person for this job in Amsterdam, please let them know there is this unique company looking for her or him. Sharing this blog-post would help a lot.
    You can find more information in this job-post:

    We all know that quality comes with attention to detail, but also that with growth the details are the first to be postponed. We seek help in handling daily operations during our growth. The most important tasks are:

    • Customer contact. You make sure the communication is regular and smooth with all our customers, making them more engaged and happy with us.
    • Sales follow up. You take over to discuss the needs of potential customers pre-sales has had contact with.
    • Team support. You help the development-teams to get even better by helping them to solve their daily and long-term problems.

    The job is very broad, but is all around a listening ear and getting things done.

    You have studied business administration or alike, and have a can-do attitude. You know how to work with technical people and are a real team-player. You understand how to develop and engage group dynamics.

    Do you think this is a job written for you, then we would like to hear more from you! Send an email to jobs@streamhpc.com with a motivational letter and listing relevant experience.

    Thanks for helping out!

    If you got sent here, we hope to hear from you!

    How to speed up Excel in 6 steps

    After the last post on Excel (“Accelerating an Excel Sheet with OpenCL“), there have been various request and discussions how we do “the miracle”. Short story: we only apply proper engineering tactics. Below I’ll explain how you can also speed up Excel and when you actually have to call us.

    Excel is a special piece of software from a developer’s perspective. An important rule of software engineering is to keep functionality (code) and data separate. Excel mixes these two as no other, which actually goes pretty well in many cases unless the data gets too big or the computations too heavy. In that case you’ve reached Excel’s limits and need to properly solve it.

    Below are the steps to go through, of which most you can do yourself! Continue reading “How to speed up Excel in 6 steps”

    Call for speakers: IEEE eScience Conference in Amsterdam

    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”

    Do you want to join StreamHPC?

    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.

      Selecting Applications Suitable for Porting to the GPU

      Assessing software is never comparing apples to apples

      The goal of this writing is to explain which applications are suitable to be ported to OpenCL and run on GPU (or multiple GPUs). It is done by showing the main differences between GPU and CPU, and by listing features and characteristics of problems and algorithms, which can make use of highly parallel architecture of GPU and simply run faster on graphic cards. Additionally, there is a list of issues that can decrease potential speed-up.

      It does not try to be complete, but tries to focus on the most essential parts of assessing if code is a good candidate for porting to the GPU.

      GPU vs CPU

      The biggest difference between a GPU and a CPU is how they process tasks, due to different purposes. A CPU has a few (usually 4 or 8, but up to 32) ”fat” cores optimized for sequential serial processing like running an operating system, Microsoft Word, a web browser etc, while a GPU has a thousands of ”thin” cores designed to be very efficient when running hundreds of thousands of alike tasks simultaneously.

      A CPU is very good at multi-tasking, whereas a GPU is very good at repetitive tasks. GPUs offer much more raw computational power compared to CPUs, but they would completely fail to run an operating system. Compare this to 4 motor cycles (CPU) of 1 truck (GPU) delivering goods – when the goods have to be delivered to customers throughout the city the motor cycles win, when all goods have to be delivered to a few supermarkets the truck wins.

      Most problems need both processors to deliver the best value of system performance, price, and power. The GPU does the heavy lifting (truck brings goods to distribution centers) and the CPU does the flexible part of the job (motor cycles distributing doing deliveries).

      Assessing software for GPU-porting fitness

      Software that does not meet the performance requirement (time taken / time available), is always a potential candidate for being ported to a GPU. Continue reading “Selecting Applications Suitable for Porting to the GPU”

      DOI: Digital attachments for Scientific Papers

      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”

      Learn about AMD’s PRNG library we developed: rocRAND – includes benchmarks

      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.

      The only problem is that CUDA-libraries need to have their HIP-equivalent to be able to port all CUDA-software.

      Here is where we come in. We helped AMD make a high-performance Pseudo Random Generator (PRNG) Library, called rocRAND. Random number generation is important in many fields, from finance (Monte Carlo simulations) to Cryptographics, and from procedural generation in games to providing white noise. For some applications it’s enough to have some data, but for large simulations the PRNG is the limiting factor. Continue reading “Learn about AMD’s PRNG library we developed: rocRAND – includes benchmarks”