The E4 Computer Engineering team has garnered a solid reputation in Europe with high performance computing solutions for customers like CERN. To learn more, we caught up with Simone Tinti, who heads up the E4 HPC Team.
“As long as setting up an energy inefficient datacentre is an economically viable option for IT equipment owners, it is unlikely that substantial progress will be made towards reversing a dangerous trend. While the issue is a planetary one, now is a good time for Europe to take it in its own hands and show the planet the way towards a more responsible and energy conscious future for the IT industry and High Performance Computing.”
In this RCE Podcast, Brock Palen and Jeff Squyres discuss the Open Compute Project with Thomas Sohmers from Rex Computing. “Thomas Sohmers is the founder and CEO of REX Computing. His experience includes working at the MIT Institute for Soldier Nanotechnologies for 3 years as both an end user of HPC systems, and later transitioning into designing and building them at the lab. This experience led to starting REX Computing in 2013 as a recipient of the Peter Thiel ’20 under 20′ Fellowship, where he leads the architectural design and business operations.”
“The end of Dennard scaling has made all computing power limited, so that performance is determined by energy efficiency. With improvements in process technology offering little increase in efficiency innovations in architecture and circuits are required to maintain the expected performance scaling. The large scale parallelism and deep storage hierarchy of future machines poses programming challenges. Future programming systems must allow the programmer to express their code in a high-level, target-independent manner and optimize the target-dependent decisions of mapping available parallelism in time and space. This talk will discuss these challenges in more detail and introduce some of the technologies being developed to address them.”
Penguin Computing just announced the Altus Altus 2a30, a building block for the first application optimized accelerated processing unit (APU) clusters, making seamless GPU and CPU memory sharing on clusters a reality based on heterogeneous system architecture (HSA) from AMD. The shared memory capability involves very lightweight context switches to switch instantaneously between the GPU and CPU, whichever code runs best at a given moment.