Large-Scale Quantum Computing Prototype on Horizon

What supercomputers will look like in the future, post-Moore’s Law, is still a bit hazy. As exascale computing comes into focus over the next several years, system vendors, universities and government agencies are all trying to get a gauge on what will come after that. Moore’s Law, which has driven the development of computing systems for more than five decades, is coming to an end as the challenge of making smaller chips loaded with more and more features is becoming increasingly difficult to do.

While the rise of accelerators, like GPUs, FPGAs and customized ASICs, silicon photonics and faster interconnects …

Large-Scale Quantum Computing Prototype on Horizon was written by Jeffrey Burt at The Next Platform.

Memristor Research Highlights Neuromorphic Device Future

Much of the talk around artificial intelligence these days focuses on software efforts – various algorithms and neural networks – and such hardware devices as custom ASICs for those neural networks and chips like GPUs and FPGAs that can help the development of reprogrammable systems. A vast array of well-known names in the industry – from Google and Facebook to Nvidia, Intel, IBM and Qualcomm – is pushing hard in this direction, and those and other organizations are making significant gains thanks to new AI methods as deep learning.

All of this development is happening at a time when the …

Memristor Research Highlights Neuromorphic Device Future was written by Jeffrey Burt at The Next Platform.

Juggling Applications On Intel Knights Landing Xeon Phi Chips

Intel’s many-core “Knights Landing” Xeon Phi processor is just a glimpse of what can be expected of supercomputers in the not-so-distant future of high performance computing. As the industry continues its march to exascale computing, systems will become more complex, and evolution that will include processors that not only sport a rapidly increasing number of cores but also a broad array of on-chip resources ranging from memory to I/O. Workloads ranging from simulation and modeling applications to data analytics and deep learning algorithms are all expected to benefit from what these new systems will offer in terms of processing capabilities. …

Juggling Applications On Intel Knights Landing Xeon Phi Chips was written by Jeffrey Burt at The Next Platform.

ARM Gains Stronger Foothold In China With AI And IoT

China represents a huge opportunity for chip designer ARM as it looks to extend its low-power system-on-a-chip (SoC) architecture beyond the mobile and embedded devices spaces and into new areas, such as the datacenter and emerging markets like autonomous vehicles, drones and the Internet of Things. China is a massive, fast-growing market with tech companies – including such giants as Baidu, Alibaba, and Tencent – looking to leverage such technologies as artificial intelligence to help expand their businesses deeper into the global market and turning to vendors like ARM that can help them fuel that growth.

ARM Holdings, which designs …

ARM Gains Stronger Foothold In China With AI And IoT was written by Jeffrey Burt at The Next Platform.

Top Chinese Supercomputer Blazes Real-World Application Trail

China’s massive Sunway TaihuLight supercomputer sent ripples through the computing world last year when it debuted in the number-one spot on the Top500 list of the world’s fastest supercomputers. Delivering 93 teraflops of performance – and a peak of more than 125,000 teraflops – the system is nearly three times faster than the second supercomputer on the list (the Tianhe-2, also a Chinese system) and dwarfs the Titan system Oak Ridge National Laboratory, a Cray-based machine that is the world’s third-fastest system, and the fastest in the United States.

However, it wasn’t only the system’s performance that garnered a lot …

Top Chinese Supercomputer Blazes Real-World Application Trail was written by Jeffrey Burt at The Next Platform.

Getting Down To Bare Metal On The Cloud

When you think of the public cloud, the tendency is to focus on the big ones, like Amazon Web Services, Microsoft Azure, or Google Cloud Platform. They’re massive, dominating the public cloud skyline with huge datacenters filled with thousands of highly virtualized servers, not to mention virtualized storage and networking. Capacity is divvied up among corporate customers that are increasingly looking to run and store their workloads on someone else’s infrastructure, hardware that they don’t have to set up, deploy, manage or maintain themselves.

But as we’ve talked about before here at The Next Platform, not all workloads run …

Getting Down To Bare Metal On The Cloud was written by Jeffrey Burt at The Next Platform.