IT/Datacenter & Super Computing - Page 3

It looks like we have finally found a system that can actually run Crysis -- the new Cerebras CS-1 system that is a new system for artificial intelligence (AI) workloads. So while it might not run Crysis, it is a powerhouse for AI developers.

Cerebras CS-1 is actually quite small considering its processing power, with the 26-inch-tall PC packing an insane 400,000 cores and an even crazier 1.2 trillion transistors. The 400,000-core processor is called the Wafer Scale Engine (WSE) which has a trillion transistors, 18GB of on-chip SRAM, and an interconnect speed of up to 1PB/sec (yeah, petabytes per second).

The exciting WSE processor is absolutely huge, where next to a keyboard it looks fake even -- but this 1.2 trillion transistor processor indeed packs 400,000 processing cores. Cerebras Systems founder Andrew Feldman explains: "The CS-1 is the industry's fastest AI computer, and because it is easy to install, quick to bring up and integrates with existing AI models in TensorFlow and PyTorch, it delivers value the day it is deployed. Depending on workload, the CS-1 delivers hundreds or thousands of times the performance of legacy alternatives at one-tenth the power draw and one-tenth the space per unit compute".

Google has reached a monumental achivement for the future of quantum processors and quantum computing, with their experimental quantum processor completing a 10,000-year task in just 3 minutes, 20 seconds.

In a blog post on Google's website, Google CEO Sundar Pichai explained that Nature published its 150th anniversary issue with the big news that Google's team of researchers have achieved a "big breakthrough in quantum computing known as quantum supremacy".

Google flexed its new quantum processing muscles to stretch and achieve that quantum supremacy, with Pichai explaining: "As we scale up the computational possibilities, we unlock new computations. To demonstrate supremacy, our quantum machine successfully performed a test computation in just 200 seconds that would have taken the best known algorithms in the most powerful supercomputers thousands of years to accomplish".

There has been tons of news around AMD's new 7nm, and Intels fight to retain market share over the past months. Today this article is all AMD as they worked with CRAY to create something truly insane.

UK Research and Innovation (UKRI) has once again contracted the team at CRAY to build their follow-up to the Archer supercomputer. Archer 2 is reported to offer up to 11x the throughput of the previous Archer supercomputer put into service back in late 2013.

Archer 2 is going to be powered by 12,000 EPYC Rome 64 Core CPUs with 5,848 compute nodes, each having two of the 64 core behemoths. The total core count is 748,544 ( 1,497,088 threads) and 1.57PB for the entire system. The CPU speed is listed as 2.2GHz, which we must assume they are running off of the base clock, so that would be EPYC 7742 CPUs with a 225W TDP. These sorts of specs are insane but also will make some significant heat. Archer 2 will be cooled by 23 Shasta Mountain direct liquid cooling and associated liquid cooling cabinets. The back end for connectivity is Cray's next-gen slingshot 100Gbps network compute groups.

Everyday we are moving one step more closer to unlocking the mystery behind quantum computing and the benefits it can provide the human race. Today is yet again another one of those days.

According to researchers out of the The Johns Hopkins University, a newly discovered superconducting material has been found to have the "properties that could be the building blocks for technology of the future." Quantum computing is the most complicated computing humans are currently working on, and if you have a general grasp of how normal computers work then you should be able to appreciate the complexity of any quantum progression.

Normal bits that are present in all traditional computers use 0 or 1 to represent an electrical voltage pulse to store information. Quantum computers which are based on the laws of quantum mechanics use quantum bits or better known as qubits. These qubits exist in both the 0 state and the 1 state, but also both states at the same time. This is called a superposition, perhaps you have heard of the famous qubit example called Schrodinger's cat?

D-Wave announced its next-gen quantum computer dubbed 'Advantage' which during the announcement, had its first customer lined up for the next wave in quantum computing.

D-Wave's new quantum computer already has its first customer with nuclear weapons research site Los Alamos National Laboratory (LANL) securing the next-gen quantum computer. This isn't LANL's first business with D-Wave either, it'll actually be their third upgrade to their in-house D-Wave quantum computer.

Los Alamos National Laboratory associate director for simulation and computation, Irene Qualters, said in a statement: "This is the third time we will have upgraded our D-Wave system. Each upgrade has enabled new research into developing quantum algorithms and new tools in support of Los Alamos' national security mission. Quantum computing is a critical area of research for Los Alamos".

The fight for quantum supremacy might have just been tipped into Google's favor, with the search giant saying it has reached a major milestone towards the development of quantum computing.

A recent paper was published and then quickly pulled on NASA's website, which read that "this experiment marks the first computation that can only be performed on a quantum processor". The research paper was titled "Quantum supremacy using a programmable superconducting processor".

Google's in-house quantum computer smashed through a calculation of a random number generator in just 3 minutes and 20 seconds, versus the world's fastest supercomputer -- Summit, which would take around 10,000 years. The authors of the paper wrote: "To our knowledge, this experiment marks the first computation that can only be performed on a quantum processor". Impressive stuff.

HPE has teamed with NASA on future supercomputer collaboration, with HPE providing its new Aitken supercomputer for future missions to the moon. HPE and NASA Ames Research Center have signed a four-year, multi-phase partnership over its Aitken supercomputer.

NASA will use HPE's new Aitken supercomputer for its Artemis program, which will see humans returning to the moon in 2024. Artemis will be handling calculations, modeling, and simulations of entry, descent, and landing (EDL) on the moon.

Inside, HPE's new Aitkin supercomputer is based on HPE's SGI 8600 HPC platform, which is a tray-based, scalable supercomputer cluster.

Scientists are always looking for more updated and better ways to understand the universe we are currently living in and one of the best ways they can do that is through simulations.

According to a new announcement by researchers at the University of Arizona, the Ocelote supercomputer has managed to generate 8 million simulated universes for scientists to study and understand. These simulated universes are going to be directly compared to our actual cosmos, and through the comparison scientists hope to draw a better conclusion of the cosmic events that occurred while also filling in missing data points that are currently puzzling to theorists.

While 8 million simulated universes in just three weeks is certainly an achievement in itself, Ocelote didn't quite have the power to render these universes to every detail, as that would require an astronomical amount of computing power. Instead, Ocelote and the scientists created a system where the computer produced results that are a "sizeable chunk" of the observable universe. It should also be noted that each of the universes created were devised under a completely different set of rules, meaning that scientists have a lot of busy comparison work to do now.

AMD has just scored a gigantic deal in that the company will power the next-gen fastest and most expensive supercomputer in the world, with the US Department of Energy buying a new AMD-powered custom supercomputer built by Cray called Frontier.

Frontier will come online in 2021 and is powered with super-fast EPYC processors and Radeon Instinct accelerators that will pump out an astonishing and record-breaking 1.5 exaflops of processing power. The system will be used for various tasks which will include performing advanced calculations in nuclear and climate research, simulating quantum computers, nuclear reactors, and more.

The new system will be delivered in late 2021 and turned on and cranking along in 2022 for the Oak Ridge National Laboratory in Tennessee. AMD has some huge bragging rights here as Frontier has as much processing power as the 160 fastest supercomputers combined -- yeah, combined.

Intel is wanting to boost the development of quantum computing technology, with the chipmaker unveiling its new Cryogenic Wafer Prober which allows researchers to test qubits on 300mm silicon wafers at super-low temperatures. Intel says this is the first quantum computing testing tool ever made, making it a very big deal.

Intel partnered up with Bluefors and Afore for the new cryoprober, with the new quantum computer testing tool made because during the development of Intel's own quantum computer, they worked out they needed a cryoprober to make it easier to test qubits in silicon before they're finalized and put into quantum chips and then sent off to customers. The company added that the cryoprober would allow the company to scale up manufacturing of silicon quantum computers, with less issues.

Quantum computers and their respective chips are normally tested for months and months in a super-low temperature dilution refrigerator where it would work out what works, and what doesn't. Normal transistors can be tested within an hour, versus months and months for quantum chips. The feedback from testing can be used to make tweaks that can be sent to manufacturing before the chips are made.

The US is home again to the world's fastest supercomputer, with Summit making its debut at the Oak Ridge National Laboratory in Oak Ridge, Tennessee. Summit is powered by NVIDIA technology, which is how it has become the best in the supercomputer business.

Inside of Summit you'll find an insane 27,648 of NVIDIA's super-fast Volta Tensor Core GPUs that is capable of 200 petaflops of computing power. Considering that the current supercomputer champion is China's Sunway TaihuLight that now only pushes 93 petaflops, Summit has truly climbed new supercomputing heights.

On top of the 27,648 Volta Tensor Core GPUs there's also 9,216 CPUs that get crammed into 5,600 square feet of cabinet space that is about the size of two tennis courts. The systems combined have an approximate weight of a commercial jet, and considering the 200 petaflops of power, this is an amazing technical achievement. Summit is capable of 3 exaops of AI, where if every single human being on Earth did 1 calculation per second, it would take 15 years... but on Summit it will take a single second.

Google has just blown the industry away with their new TPU 3.0, their next-gen custom-designed processor that is ridiculously over-powered to train machine learning systems.

TPU 3.0 is 8x faster than its predecessor, with the first TPU being released in 2015, the company has made leaps and bounds. A pod of TPU 2.0s packed ASICs that featured 64GB of HBM that pumped out 2.4TB/sec, which is pretty insane. In comparison, the Radeon RX Vega 64 with 8GB of HBM2 is capable of 512GB/sec memory bandwidth.

Google should be the new AI chip champion with its TPU 3.0 ready for TensorFlow use, as well as a refined push into the cloud from Google. The new TPU 3.0 chips are so next-level that they require and use liquid cooling to keep them cool, but provide a huge 100 PFLOPs of machine learning power... crazy stuff.

Intel is hard at work on the research and development side of its upcoming Nervana Neural Network Processor, a new chip that will blow away any general-purpose processor for machine learning and AI applications.

Vice President of Hardware for Intel's Artificial Intelligence Products Group, Carey Kloss, has provided an update to the work Intel has made on the NNP.

What does a neural network processor (NNP) have to do? In order to train a machine using neural networks needs a gigantic amount of memory and arithmetic operations in order to generate useful output. Then we step into the scaling capabilities, power consumption and maximum utilization being the cornerstones of Intel's Nervana.

During the recent Amazon Web Services re:Invent conference in Las Vegas on Wednesday, AWS boss Andy Jassy announced that the company will be enabling a suite of AI-powered tools. Jassy told the audience of over 40,000 people: "We have to solve the problem of making [AI] accessible for everyday developers and scientists".

These new cloud-based AI tools will be capable of measuring sentiment, tracking people in live feeds, translating languages, and much more. The list of things that the new AI enabled services AWS has is scary good, check them out:

I thought that Skynet would open up in the US, but it looks like the Terminators will want some bacon and maple syrup instead, with Google announcing its new DeepMind AI research lab is open for... well... business I guess, in Canada.

DeepMind has announced that it's new AI research lab is opening up in Edmonton, Alberta later this month, with three University of Alberta computer science professors (Richard Sutton, Michael Bowling and Patrick Pilarski) leading the group. They will be joined by seven other AI leaders, too. The big question is: why isn't Google's new AI digs opening up on US soil? Recode reports that there are familiarity and political considerations, with over a dozen University of Alberta grads working at DeepMind, and Sutton was one of the first to join the AI lab as an advisor.

The Canadian government is also more willing to invest in AI research, with Canada cozying up to AI scientists to the tune of $125 million in funding - on top of existing funding. On US soil, the Trump administration is swaying away from scientific research, proposing major funding cuts.

It appears that Skynet wants us all on Big Pharma drugs, with British pharmaceutical giant GlaxoSmithKline (GSK) looking to AI to design better, more efficient - and I'm sure, more profitable drugs.

GSK announced a new partnership with Exscientia, a British company that specializes in drug design. The two will work toegther to use Exscienta's AI-enabled platform to discover new, high-quality drug candidate-quality molecules. GSK has tasked Exscientia to work on 10 specific disease-related targets, and if they hit those targets, GSK will write a cheque for $43 million in research payments.

The partnership will see the companies tapping into the power of supercomputers and machine learning in order to see how new compounds will behave, and by speeding this process up with the help of crazy amounts of computing power aided by AI, it will save the company both time and money. Human researchers are nowhere near as efficient as AI and supercomputers working every second of every day with a billion things going on at once, which could mark a very big change for medicine.

AMD's EPYC lineup of processors is here and ready to compete with Intel's next generation of server-ready products.

The AMD EPYC 7000 series processors will offer up to 32 "Zen" cores, which were designed to fit into this space. Each processor will have eight DDR4 channels, support for a whopping 2TB of memory, 128 PCI-E lanes, a dedicated security subsystem, and there will be no chipset outside of the CPU. The motherboard socket will also be compatible with the next generation of EPYC processors, in the hope that more vendors will jump on board.

There are going to be nine dual-socket SKUs that go all the way from 8 cores and 16 threads to 32 cores and 64 threads at 3.2GHz. TDPs will range up to 180W (that includes chipset too), and all processors will feature eight memory channels and 128 PCI-E lanes, so there is no compromise. The way AMD can scale EPYC is through their Infinity Fabric, which helps them scale past Moore's Law.

You'd think that the US would lead the supercomputer race, but it's China that is dominating right now. According to the latest TOP500 ranking of the world's most powerful supercomputers, the US has fallen so far behind it's at 1996 levels.

The list is updated twice a year, and determines the rankings of the supercomputer by overall computing power. China has the top two spots with its Sunway TaihuaLight pushing an incredible 93 petaflops, while the Tianhe-2 is capable of 33.9 petaflops. The US only has its Department of Energy's Titan supercomputer, with just 17.6 petaflops of computing power in comparison.

The newly upgraded Swiss National Supercomputing Centre has some power on the new list, pushing out 19.6 petaflops - beating the Titan in the US, up from its previous power of 9.8 petaflops. The US is no longer in the top three supercomputer rankings, falling into fourth place for the ifrst time in over 20 years.

China is working on the next generation of supercomputers, with plans to have a prototype exacale computer by the end of 2017. The country wants to be the first to build a supercomputer capable of a billion, billion calculations per second.

If they can do this, China would propel themselves to #1 in the world of supercomputing - beating out what was the world's fastest supercomputer, the Sunway TaihuLight machine, which came to life in June 2016.

China became a country to look to for supercomputers, as they made their supercomputer using locally made chips - versus products from US companies like AMD, Intel, or NVIDIA. Exascale computers on the other hand, are magnitudes more powerful - capable of 1 quintillion calculations per second (a billion, billion - so, like, really fast).

HP has unveiled its new supercomputer, simply called The Machine, something first announced back in 2014. HP is aiming to smash all previous technology in existence with The Machine, as their new supercomputer doesn't need to rely on traditional processors - instead, it will utilize memory for its brute speed.

HP Enterprise explains that The Machine is up to 8000x faster than traditional machines (you'd freakin' hope so), but it's still years away from being released. HP will be aiming at high-end servers for companies like Google and Facebook, with the architecture itself powered by memory-driven computing, we should see this type of memory-driven PC trickle down to the PC one day, I hope.

The Machine uses photonics to transmit data using light, and thanks to its massive, and super-fast memory pool - The Machine can really crank through those datasets. When the data needs to be transferred between processors, things slow down - but HP has thought ahead of time using memory to super-speed the supercomputer.