If you're interested in our progress over the last year or hoping to ask us questions about our plans for the future, don't miss the chance to talk with our own Niclas Jansson at the first poster session of the Euro HPC Summit on Tuesday, March 19th!
Knowledge Shared is Knowledge Gained: the 1st CEEC Community Workshop This past December 13th, CEEC held its first annual community workshop at our consortium partner Friedrich-Alexander-Universität in Erlangen, Germany and…
Until recent years, linear algebra solvers were predominantly operating with double precision or binary64. With the advent of AI, in particular deep learning, lower floating-point precisions formats were introduced to…
It’s been a while since our last update, and we’re still in the early days of our work. That said, we’ve been travelling to introduce ourselves and present some of the work we’ll be building on during our 4 project years. Maybe you’ve seen us? This summer we had various presentations both at ISC High-Performance and at the Platform for Advanced Scientific Computing (PASC) conference
The third in a series of presentations from Roman Iakymchuk on work using tools to investigate mixed precision possibilities. He and his co-author Pablo de Oliveira Castro introduce an approach to address the issue of sustainable computations with computer arithmetic tools. They use the variable precision backend (VPREC) to identify parts of code that can benefit from smaller floating-point formats and show preliminary results on several proxy applications.
Energy consumption constraints for large-scale computing encourage scientists to revise the architecture design of hardware but also applications, algorithms, as well as the underlying working/ storage precision. I will introduce an approach to address the issue of sustainable, but still reliable, computations from the perspective of computer arithmetic tools. We employ VerifiCarlo and its variable precision backend to identify the parts of the code that benefit from smaller floating-point formats. Finally, we show preliminary results on proxies of CFD applications.
What is Mixed Precision? Computers have been getting faster for as long as they’ve existed. However, not every computer part has been speeding up at the same rate. For example,…
In this talk, Roman Iakymchuk presents his work on accuracy and reproducibility assuring strategies for parallel iterative solvers that may not hold due to the non-associativity of floating-point operations. These strategies primarily rely on guarding every bit of result until final rounding, hence they can be costly. The energy consumption constraint for large-scale computing encourages scientists to revise the architecture design of hardware but also applications, algorithms, as well as the underlying working/ storage precision. The main aim is to make the computing cost sustainable and apply the lagom principle (''not too much, not too little, the right amount"), especially when it comes to working/ storage precision. Thus, he will introduce an approach to address the issue of sustainable, but still reliable, computations from the perspective of computer arithmetic tools. Before lowering precision, one must ensure that the simulation is numerically correct, e.g. by relying on alternative floating-point models/ rounding to pinpoint numerical bugs and to estimate the accuracy. We employ VerifiCarlo and its variable precision backend to identify the parts of the code that benefit from smaller floating-point formats. Finally, we show preliminary results on proxy applications.