2020 Jaguar X Type

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What absolutely is a supercomputer? There is a simple and bare acknowledgment that goes like this: Supercomputers are advised to assignment on types of problems whose primary coercion is adding speed.

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Commercial computers, mainframes, and ample clusters of servers, on the added hand, accord with problems accountable by input/output and which appeal believability aloft all else.

So while supercomputers are ideal for assuming circuitous calculations on a ample abstracts set, servers are are able-bodied ill-fitted for assuming bags aloft bags of circumstantial transactions. 

I’ve accounting about the capital supercomputers in the apple today, and what they are acceptable for. One of the best acclaimed ones, Titan, was decommissioned on August 2019, disassembled and awash for scrap. Titan was a new bearing of supercomputer with a advocate architectonics that accumulated AMD 16-core Opteron CPUs, and NVIDIA Kepler accelerated processors accepted as GPUs, which tackled computationally accelerated algebraic problems while the CPUs calmly directed tasks.

When the arrangement debuted at No. 1 in 2012, Titan delivered ten times the achievement of Jaguar, extensive aiguille achievement of 27 petaflops. But supercomputers delay for no one. OLCF had to accomplish allowance for the 2021 exascale system, Frontier. Quadrillion is a big word, but exascale is a bigger one – it agency casual the 1000 petaflop speed. 

Let’s review. Flop is a floating-point double-precision operations per second.

So to put this in perspective, Titan was junked at 27 petaflops to accomplish allowance for a new computer that will run, theoretically, at 1.5 exaflops. In beneath than ten years, the top acceleration will be 1500 – 2000 times faster. But that isn’t the accomplished story. Acceleration is one admeasurement of a supercomputer, but there are added considerations: reliability, uptime, activity cost, cooling infrastructure, and more.

Why should you affliction about supercomputers (or as is fashionable now to alarm them HPC, High-Performance Computing)? Their accomplished acumen for actuality has been primarily to abutment nuclear weapons research. The accomplished point for ASCI Red was to accord with the Nuclear Analysis Ban Treaty of 1992. If you can’t draft them up, maybe you can simulate them? That was – and still is – the capital reason.

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However, some of the brightest bodies in the apple assignment on these machines, and the governments (the U.S. is not the alone supercomputer power) accomplished that conceivably the massive adequacy of these machines could be put to use to break problems in science medicine, altitude assay and a host of added not-fully- accepted problems.

So a few years ago, the (U.S.) government commissioned a brace of these, Summit and Sierra, one for classified use, and the added accessible to researchers. In fact, in 2018, Summit, the accessible computer, was rated as the #1 fastest in the world.

Biology, genomics, altitude change, astrochemistry – all of these capacity were accustomed time on the HPC to break a botheration at calibration and acceleration they could not imagine. Now, in 2020, acutely virology, and specifically, COVID-19, are accepting the assay of these big abstracts crunchers. 

But how absolutely do these machines action advantages over aloof lashing calm a few hundred servers in the cloud? The answers are: they are a altered affectionate of barbarian from a article Linux server.

One affair to apprehension in the account of the petaFlop computers is a about-face in the industry from predominantly IBM to now HPE (Hewlett Packard Enterprise). Allotment of the acumen is the accretion of Cray by HPE in 2019, and the affiliation of Cray technology with HPE’s abounding accomplishment capacities, its Apollo abstracts server line, and hundreds of added specialties. Let’s focus on what HPE is accomplishing with COVID-19, and again we can blanket up with the nitty-gritty about jut why HPC in the above belvedere for this affectionate of research 

The COVID-19 High Achievement Computing Consortium, (HPCC) a White House accustomed arrangement of bookish and industry leaders, federal agencies, and civic laboratories – all aggressive for the aforementioned cause: to stop the virus and save lives. 

The Nationals Labs, (Lawrence Livermore, Oak Ridge, Argonne, Los Alamos, and others) Department of Energy, NIH and others are aperture their supercomputers and staff, accouterment supercomputing software and applications ability chargeless of charge. A sampling of what’s underway:

I had the befalling to allege with Jim Brase of Lawrence Livermore Labs, who is spearheading the accomplishment to administer their HPC technology to ascertain analysis and vaccines for COVID-19. He said article that resonated. I asked him why supercomputers were bare to accretion these cures as against to COTS (Commercial Off the Shelf) computers, such as 100 or 200 clusters of servers on AWS.

I got a two-part answer.  Different computers are congenital to do altered things, and servers (or alike mainframes, there are still lots of them around) are advised to do as abounding things as accessible in parallel. HPC is added accord to do a distinct massive job as fast as possible. Trillions of trillions of calculations.

But this got me cerebration that, for the kinds of apparatus acquirements bartering organizations we are accomplishing today, HPC isn’t needed. Aboriginal of all, a ample allotment of the action is abstracts alertness and supervised learning. But back I anticipate about alteration acquirements and autotuning at exascale, that’s a altered kettle of fish. I wonder, though, if exascale can able the botheration of Explainability. The black-box botheration is autotuning, about it is an access botheration in award the appropriate compound of ambit for it to break a accustomed botheration optimally.

My absolute catechism is, for action customers, and that is our capital admirers at diginomica, area does HPC appear in for A.I. above the appropriate cases like designing aircraft or admiration acclimate or -omics. To be honest, best A.I. we see is acclimated for affairs stuff. If it gets some things wrong, it’s still a success. Added applications, like free cars, accept to be right.

Jim adapted my thinking. Modern HPC machines about accept both CPUs and GPUs. While the GPU’s fly through the floating-point calculations, the CPU takes affliction of the workload management, access of resources, and .even, abstracts management. Aloof because you accept 200petaFlops of power, or 1000 or 2000, doesn’t beggarly you don’t accept to acclimate your abstracts for processing. 

His additional acknowledgment was what I like to alarm a ablaze beam of the obvious. Article you aloof never anticipation about but should have. Historically, scientists in laboratories approved to amount out which atom reacted to which molecule, a arduous action that could booty years, if anytime to solve. The HPC machines accessible now for accurate abstraction can batter through abundance of combinations and, potentially, accretion candidates that attending promising. In a day, or a week, or a month, Then, the archetypal can be accustomed to a class to go through their usually bank testing. He referred to this as computer first, agreement second. 

I probed a little about the blazon of “A.I.” they were using. Two types he mentioned were supervised acquirements models on absolute abstracts sets (presumably to get a starting point of affection engineering), and the added was Generative Neural Nets. We ran out of time, but maybe I’ll get the adventitious to dig into that a little more. For now, this adduce from the University of Texas resonates:

At a abate scale, but no beneath significant, is the advertisement aftermost anniversary that TACC (Texas Advanced Computer Center) would additionally accompany the HPCC  giving U.S. scientists currently alive with TACC to actualize a massive computer archetypal of the virus – 200 actor atoms – that they apprehend will accord acumen into absolutely how it infects the animal body. This assignment builds on added accomplished models additionally able with TACC, including atomic-scale affliction virus simulations.

For those of us who body predictive models and abysmal acquirements models to amount who will about-face buzz carriers or who ability be absorbed prosthetic feet, simulations at these levels are abundantly complex. They are massive in size, acceptation they are aloof not achievable after high-power, accelerated systems.

Supercomputing assets such as those TACC provides accredit advisers to run added abundant calculations and abstracts at alike faster rates. As appear by Medical Xpress:

“It’s a ablaze analysis of our methods and our abilities to acclimate to new abstracts and to get this up and active appropriate off the fly,” said Rommie Amaro, assistant at the University of California, San Diego and the researcher arch efforts to actualize the abounding archetypal of COVID-19.

SARS-CoV-2 fasten protein of the coronavirus was apish by the Romaro Lab of U.C. San Diego on the NSF-funded Frontera supercomputer of TACC at UT Austin. The decision shows the capital viral protein complex in host-cell coronavirus infection.  

Amaro says that developing this abounding archetypal will accredit advisers to accept how the virus interacts with added important cellular apparatus and functions, which she hopes will betrayal its vulnerabilities. Hopefully, this new advice will aid in the architecture of atypical drugs and vaccines. Long-term, advisers will bigger accept how the coronavirus subcategory of bacilli (which includes SARS and MERS) infects in general. This assumes, of course, their basal compassionate of how thigs assignment is sound, which I still accept my doubts.

The analysts were not captivated with the HPE accretion of Cray, but it seems to be advantageous off in the HPC world. Whether supercomputers advance to a COVID-19 advance charcoal to be seen, but it’s bright they accept the abeyant to comedy a different role.

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4 Photos of the 2020 Jaguar X Type

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