While considering a switch to the cloud, many of you may wonder how ANSYS licensing will work there, and more in particular, when and how we will support a pay-per-use model. I have very good news for you. Along with your existing licenses, you can use our newly announced ANSYS Elastic LicensingTM. This is a new pay-per-use licensing model unlocking virtually every ANSYS product that is supported on cloud-hosting partner hardware. Continue reading
Based on a recent announcement that ANSYS and Cray has smashed supercomputing records, an editor of a well-known magazine followed up on and asked me whether this achievement might help to compensate the slowdown of Moore’s Law. Although I was able to briefly respond, it was also end of the day and while driving home the question stayed in my head and was the origin of this blog. Continue reading
When one of my friends asked me on Saturday night what I like about my job, I started off by saying that “there is never a dull moment in high-performance computing. The computing landscape is constantly changing, the HPC ecosystem collaborations are so numerous and intriguing, and the strategic/economic value of HPC for simulation has never been greater” (or: relevance of HPC for organizations to become more competitive is so compelling).
All of this was very evident at last week’s ISC conference — one of world’s largest high-performance computing events — drawing this year over 2,800 attendees from 56 countries. Let me share with you a few exciting HPC trends observed during this conference.
Today, we announced our new ANSYS Enterprise Cloud solution, a combined service and software solution designed to help our global accounts move simulation into the public cloud. Based on my own discussions with customers, the solution is well-matched to current trends and business challenges. Let me explain. Continue reading
In a previous blog, I was expressing our privilege of having a strong HPC technology partnership with NVIDIA. Earlier this week, we announced a supercomputing milestone of scaling to 36,000 cores with fluid dynamics simulations being achieved thanks to a strategic partnership with the National Center for Supercomputing Applications (NCSA). Now, you may wonder what the relevance of this achievement is for you when you don’t have access to a supercomputer. Continue reading
In the first part of this two-part post about high-performance computing, I already addressed three commonly-held myths associated with HPC. Now I’ll address three myths that are related to particular concerns about HPC adoption.
Myth #4: “Without internal IT support, HPC cluster adoption is undoable” Continue reading
Looking back at my notes from conversations with many engineers during our recent ANSYS Convergence Conferences, I must admit that I still came across some myths and misconceptions about high-performance computing (HPC) for engineering simulation. Let me share six really striking ones with you:
- HPC is available on supercomputers only
- HPC is only useful for CFD simulations
- I don’t need HPC – my job is running fast enough
- Without internal IT support, HPC cluster adoption is undoable
- Parallel scalability is all about the same, right?
- HPC software and hardware are relative expensive
As each week begins, I realize what a privilege it is to work with leading HPC technology providers like Intel, NVIDIA, Dell, HP, IBM and many others. Apart from the pleasant inter-social aspects of our weekly meetings, these collaborations enable us to provide simulation solutions optimized on the latest computing platforms. I strongly believe this is necessary because the computing landscape changes so quickly. Our customers want to take advantage of the latest HPC technologies and expand the scope of what they can accomplish with simulation.
One example of a strong partnership is NVIDIA. As a result of this partnership, ANSYS and NVIDIA have developed GPU-accelerated solvers and algorithms across our full range of multiphysics solutions. We were one of the first commercial engineering simulation providers to introduce structural mechanics support of GPU computing, and we released the first major commercial GPU-accelerated fluid dynamics solver of its kind with ANSYS 15.0. Continue reading
In my July blog, I wondered if our customers considered moving forward with robust design practices. Since that time, I’ve found an increasing number of customers embracing and, more importantly, benefiting from these techniques. I’d like to give you a few examples that I think will appeal to you.
First of all, let’s look at ANSYS customer Brose, a tier-one supplier specializing in developing and manufacturing mechatronic systems and electric drives for automobile bodies and interiors. Every year Brose supplies millions of window regulators to many automobile manufacturers. As you can read in this article, Brose engineers adopted robust design practices using ANSYS Mechanical and Dynardo’s optiSLang software so they could ensure the robustness of their window mechanisms for a wide variety of car models and assembly conditions. Continue reading
We just published a new ANSYS Advantage magazine issue that deals with product integrity and robust design practices, and my work brought to mind a story I want to share with you. I had a first-generation LCD display in the rear-view mirror of my last car. This device was very handy to access GPS as the display showed in the mirror and didn’t require any alterations to my built-in audio system nor an unattractive GPS mount on my windshield. However, on this particular day, the display seemed to fail when I was in the middle of nowhere trying to find my way.
It is likely this malfunction occurred for a number of reasons. The combination of my heat-absorbing black car, driving in the south of Italy where the temperatures can reach up to 60° C, and the time it takes to cool the interior after switching on my air-conditioning, might not have been the parameters the equipment designer tested prior to production. Although I liked the functionality of the GPS, this product didn’t work in the real environment in which it needed to perform. Continue reading