Cray Unveils Shasta, Lands NERSC-9 Contract

By Tiffany Trader

October 30, 2018

Cray revealed today the details of its next-gen supercomputing architecture, Shasta, selected to be the next flagship system at NERSC. We’ve known of the code-name “Shasta” since the Argonne slice of the CORAL project was announced in 2015 and although the details of that plan have changed considerably, Cray didn’t slow down its timeline for Shasta. Set for commercial launch in late 2019, the exascale-class architecture unifies the Cray supercomputer and cluster product lines and debuts a brand-new Cray-designed system interconnect, called Slingshot.

In tandem with Cray’s Shasta disclosures, the U.S. Department of Energy (DOE) is announcing that NERSC, the National Energy Research Scientific Computing Center, has chosen a Cray Shasta supercomputer for its NERSC-9 system, slated for delivery in late 2020. Named “Perlmutter” (after Nobel Prize winning astrophysicist Saul Perlmutter), the system will feature AMD Epyc processors and Nvidia GPUs offering a combined peak performance of ~100 petaflops and a sustained application performance equivalent to about 3X that of the Cray Cori (NERSC-8) supercomputer. The new contract, which includes a Cray Clusterstor storage system, is worth a reported $146 million, one of the largest in Cray’s history. (We’ll be reporting additional details of the NERSC-9 system soon.)

Cray’s Steve Scott

Shasta will be the first Cray architecture to support multiple cabinet types, a 19” air- or liquid-cooled, standard datacenter rack and a high-density, liquid-cooled rack designed to hold 64 compute blades with multiple processors per blade. Both options can scale to well over 100 cabinets, according to Cray.

Currently Cray’s product set is divided between its CS line — dating to its Appro acquisition and featuring commodity software, a third-party interconnect and a standard 19” rack — and its flagship XC line, the dense, scale-optimized, liquid-cooled rack offering that integrates its custom Aries interconnect and a custom software stack. Shasta breaks this convention and allows the user to have the Cray custom interconnect and software stack in either form factor. Shasta also emphasizes infrastructure choice, offering from one to 16 nodes per compute blade, support for x86 (Intel and AMD), Arm (Marvell), GPUs (Nvidia and AMD) in the same system, as well as system interconnects from Cray (Slingshot), Intel (Omni-Path) or Mellanox (InfiniBand). Cray also supports FPGAs and anticipates offering support for one or more of the emerging ML accelerators in the next one-to-two years.

“We designed Shasta with both extreme performance and flexibility,” comments Cray CTO Steve Scott in an interview with HPCwire. “The new system architecture is motivated by increasingly heterogeneous data-centric workloads. We’re seeing more and more customers wanting to run workflows containing simulation and analytics and AI, and we needed systems that could handle all of these simultaneously, moving away from the siloed situation of different systems optimized for different workloads.”

The new architecture has the ability to handle high processor power levels with direct liquid cooling, supporting W4-class warm water cooling (up to 45-degree Celsius water). Per cabinet cooling tops out at 250 kilowatts initially, increasing to 300 kilowatts per cabinet within the first year after launch, according to Cray.

Introducing Slingshot, Cray’s 8th Generation HPC Network

One of the biggest hardware revelations in the Shasta unveiling is a new interconnect, called Slingshot, designed to scale to exascale and beyond with support for over 250,000 end points. The heart of slingshot is a 64-port switch with 200 Gbps ports (based on 50 Gbps signalling technology), providing 12.8 Tbps bandwidth per switch. Slingshot implements the Dragonfly topology, which Cray invented in 2008. Cray reduced the network diameter from five hops in the current Cray XC generation Dragonfly topology, to three hops for Slingshot, with a reported latency of around 300 nanoseconds per hop.

“Fewer hops results in lower latency, reliability goes up, and the adaptive routing gets that much better because at the place where you’re making the routing decisions you’ve got a pretty good idea of the global state of the network because of the really low diameter and because our switches exchange information with each other about the state of congestion in the network,” says Scott.

Slingshot is said to be highly configurable in that it can accommodate different node sizes and can vary the amount of network injection bandwidth to match workloads. Cray also made Slingshot Ethernet compatible to enable interoperability with third-party storage devices and datacenters in support of today’s greater need for data exchange between platforms.

Scott is especially proud of Slingshot’s novel congestion control mechanism, claimed to dramatically reduce queuing latency in the network. Scott says this is where, in practice, most latency actually comes from and the mechanism provides strong performance isolation between workloads. He adds that this is something that’s notoriously difficult to do and no one has done it yet for HPC workloads.

“There are existing congestion control mechanisms designed for datacenters and they are particularly difficult to tune. They are fragile. They are slow to converge and they just don’t work well for HPC workloads. We’ve cracked the code and figured out how to do this with Slingshot,” says Scott. “It means you’re going to get low latency, both for average latency and tail latency (the latency that the slowest 1 percent or tenth of a percent of packets experience). In traditional HPC systems, Cray’s current systems included, one workload that causes congestion can really interfere with other workloads running on the system and cause those latencies and especially those tail latencies to go off, so Slingshot’s really going to provide performance isolation and provide low and consistent network latency.”

All Together Now

Scott adds that another key part of their data-centric design is having a really strong I/O and storage system. With Shasta, Cray takes the storage system, which typically has been external to the supercomputer, and pulls it into the supercomputer directly onto the high-speed Slingshot network, obviating the need for L net router nodes and external InfiniBand network. “We will have high-performance flash and hard drive based storage enclosures that attach directly onto the Slingshot network. This reduces complexity, reduces latency and really improves the performance, especially for fine-grained I/O,” says Scott, adding that a high-performance flash tier plus a high capacity hard-drive based tier will be unified in the same Lustre namespace with tiering between them.

“Cray is widely seen as one of only a few HPC vendors worldwide that is capable of aggressive technology innovation at the system architecture level,” said Steve Conway, Hyperion Research senior vice president of research, in support of today’s announcement. “Cray’s Shasta architecture closely matches the wish list that leading HPC users have for the exascale era, but didn’t expect to be available this soon. This is truly a breakthrough achievement.”

Another vote of confidence came from Dr. Sudip Dosanjh, director of the NERSC Center at Lawrence Berkeley National Laboratory, where a Shasta system with a mix of AMD Epyc CPUs and Nvidia GPUs will be supporting a diverse set of HPC workloads.

NERSC Edison Cray XC30 supercomputer, accepted in 2013 and scheduled to be retired on March 31, 2019. Edison was one of the first “Cascade” XC systems delivered by Cray.

“Our scientists gather massive amounts of data from scientific instruments like telescopes and detectors that our supercomputers analyze every day,” said Dosanjh. “The Shasta system’s ease of use and adaptability to modern workflows and applications will allow us to broaden access to supercomputing and enable a whole new pool of users. The ability to bring this data into the supercomputer will allow us to quickly and efficiently scale and reduce overall time to discovery.  We value being able to work closely with Cray to provide our feedback on this next generation system which is so critical to extending our Center’s innovation.”

It’s been a few years and a few technology generations since we’ve seen AMD+Nvidia together in a leadership-class system, but Cray notes that there was no technical challenge or special work required to use AMD CPUs with Nvidia GPUs. “Both are designed well to work with other components, and Cray’s programming environment is well suited for targeting them,” a company spokesperson told us.

Cray expects to share specific product information and system names next spring in anticipation of making Shasta systems commercially available by the end of 2019. Cray will be showcasing Shasta and Slingshot next month (Nov. 11-16) at the 30th anniversary of the Supercomputing (SC) conference in Dallas, Texas.

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

Simulating Car Crashes with Supercomputers – and Lego

October 18, 2019

It’s an experiment many of us have carried out at home: crashing two Lego creations into each other, bricks flying everywhere. But for the researchers at the General German Automobile Club (ADAC) – which is comparabl Read more…

By Oliver Peckham

NASA Uses Deep Learning to Monitor Solar Weather

October 17, 2019

Solar flares may be best-known as sci-fi MacGuffins, but those flares – and other space weather – can have serious impacts on not only spacecraft and satellites, but also on Earth-based systems such as radio communic Read more…

By Oliver Peckham

Federated Learning Applied to Cancer Research

October 17, 2019

The ability to share and analyze data while protecting patient privacy is giving medical researchers a new tool in their efforts to use what one vendor calls “federated learning” to train models based on diverse data Read more…

By George Leopold

Using AI to Solve One of the Most Prevailing Problems in CFD

October 17, 2019

How can artificial intelligence (AI) and high-performance computing (HPC) solve mesh generation, one of the most commonly referenced problems in computational engineering? A new study has set out to answer this question and create an industry-first AI-mesh application... Read more…

By James Sharpe

NSB 2020 S&E Indicators Dig into Workforce and Education

October 16, 2019

Every two years the National Science Board is required by Congress to issue a report on the state of science and engineering in the U.S. This year, in a departure from past practice, the NSB has divided the 2020 S&E Read more…

By John Russell

AWS Solution Channel

Making High Performance Computing Affordable and Accessible for Small and Medium Businesses with HPC on AWS

High performance computing (HPC) brings a powerful set of tools to a broad range of industries, helping to drive innovation and boost revenue in finance, genomics, oil and gas extraction, and other fields. Read more…

HPE Extreme Performance Solutions

Intel FPGAs: More Than Just an Accelerator Card

FPGA (Field Programmable Gate Array) acceleration cards are not new, as they’ve been commercially available since 1984. Typically, the emphasis around FPGAs has centered on the fact that they’re programmable accelerators, and that they can truly offer workload specific hardware acceleration solutions without requiring custom silicon. Read more…

IBM Accelerated Insights

How Do We Power the New Industrial Revolution?

[Attend the IBM LSF, HPC & AI User Group Meeting at SC19 in Denver on November 19!]

Almost everyone is talking about artificial intelligence (AI). Read more…

What’s New in HPC Research: Rabies, Smog, Robots & More

October 14, 2019

In this bimonthly feature, HPCwire highlights newly published research in the high-performance computing community and related domains. From parallel programming to exascale to quantum computing, the details are here. Read more…

By Oliver Peckham

Using AI to Solve One of the Most Prevailing Problems in CFD

October 17, 2019

How can artificial intelligence (AI) and high-performance computing (HPC) solve mesh generation, one of the most commonly referenced problems in computational engineering? A new study has set out to answer this question and create an industry-first AI-mesh application... Read more…

By James Sharpe

NSB 2020 S&E Indicators Dig into Workforce and Education

October 16, 2019

Every two years the National Science Board is required by Congress to issue a report on the state of science and engineering in the U.S. This year, in a departu Read more…

By John Russell

Crystal Ball Gazing: IBM’s Vision for the Future of Computing

October 14, 2019

Dario Gil, IBM’s relatively new director of research, painted a intriguing portrait of the future of computing along with a rough idea of how IBM thinks we’ Read more…

By John Russell

Summit Simulates Braking – on Mars

October 14, 2019

NASA is planning to send humans to Mars by the 2030s – and landing on the surface will be considerably trickier than landing a rover like Curiosity. To solve Read more…

By Staff report

Trovares Drives Memory-Driven, Property Graph Analytics Strategy with HPE

October 10, 2019

Trovares, a high performance property graph analytics company, has partnered with HPE and its Superdome Flex memory-driven servers on a cybersecurity capability the companies say “routinely” runs near-time workloads on 24TB-capacity systems... Read more…

By Doug Black

Intel, Lenovo Join Forces on HPC Cluster for Flatiron

October 9, 2019

An HPC cluster with deep learning techniques will be used to process petabytes of scientific data as part of workload-intensive projects spanning astrophysics to genomics. AI partners Intel and Lenovo said they are providing... Read more…

By George Leopold

Optimizing Offshore Wind Farms with Supercomputer Simulations

October 9, 2019

Offshore wind farms offer a number of benefits; many of the areas with the strongest winds are located offshore, and siting wind farms offshore ameliorates many of the land use concerns associated with onshore wind farms. Some estimates say that, if leveraged, offshore wind power... Read more…

By Oliver Peckham

Harvard Deploys Cannon, New Lenovo Water-Cooled HPC Cluster

October 9, 2019

Harvard's Faculty of Arts & Sciences Research Computing (FASRC) center announced a refresh of their primary HPC resource. The new cluster, called Cannon after the pioneering American astronomer Annie Jump Cannon, is supplied by Lenovo... Read more…

By Tiffany Trader

Supercomputer-Powered AI Tackles a Key Fusion Energy Challenge

August 7, 2019

Fusion energy is the Holy Grail of the energy world: low-radioactivity, low-waste, zero-carbon, high-output nuclear power that can run on hydrogen or lithium. T Read more…

By Oliver Peckham

DARPA Looks to Propel Parallelism

September 4, 2019

As Moore’s law runs out of steam, new programming approaches are being pursued with the goal of greater hardware performance with less coding. The Defense Advanced Projects Research Agency is launching a new programming effort aimed at leveraging the benefits of massive distributed parallelism with less sweat. Read more…

By George Leopold

Cray Wins NNSA-Livermore ‘El Capitan’ Exascale Contract

August 13, 2019

Cray has won the bid to build the first exascale supercomputer for the National Nuclear Security Administration (NNSA) and Lawrence Livermore National Laborator Read more…

By Tiffany Trader

AMD Launches Epyc Rome, First 7nm CPU

August 8, 2019

From a gala event at the Palace of Fine Arts in San Francisco yesterday (Aug. 7), AMD launched its second-generation Epyc Rome x86 chips, based on its 7nm proce Read more…

By Tiffany Trader

Ayar Labs to Demo Photonics Chiplet in FPGA Package at Hot Chips

August 19, 2019

Silicon startup Ayar Labs continues to gain momentum with its DARPA-backed optical chiplet technology that puts advanced electronics and optics on the same chip Read more…

By Tiffany Trader

Using AI to Solve One of the Most Prevailing Problems in CFD

October 17, 2019

How can artificial intelligence (AI) and high-performance computing (HPC) solve mesh generation, one of the most commonly referenced problems in computational engineering? A new study has set out to answer this question and create an industry-first AI-mesh application... Read more…

By James Sharpe

D-Wave’s Path to 5000 Qubits; Google’s Quantum Supremacy Claim

September 24, 2019

On the heels of IBM’s quantum news last week come two more quantum items. D-Wave Systems today announced the name of its forthcoming 5000-qubit system, Advantage (yes the name choice isn’t serendipity), at its user conference being held this week in Newport, RI. Read more…

By John Russell

Chinese Company Sugon Placed on US ‘Entity List’ After Strong Showing at International Supercomputing Conference

June 26, 2019

After more than a decade of advancing its supercomputing prowess, operating the world’s most powerful supercomputer from June 2013 to June 2018, China is keep Read more…

By Tiffany Trader

Leading Solution Providers

ISC 2019 Virtual Booth Video Tour

CRAY
CRAY
DDN
DDN
DELL EMC
DELL EMC
GOOGLE
GOOGLE
ONE STOP SYSTEMS
ONE STOP SYSTEMS
PANASAS
PANASAS
VERNE GLOBAL
VERNE GLOBAL

A Behind-the-Scenes Look at the Hardware That Powered the Black Hole Image

June 24, 2019

Two months ago, the first-ever image of a black hole took the internet by storm. A team of scientists took years to produce and verify the striking image – an Read more…

By Oliver Peckham

Intel Confirms Retreat on Omni-Path

August 1, 2019

Intel Corp.’s plans to make a big splash in the network fabric market for linking HPC and other workloads has apparently belly-flopped. The chipmaker confirmed to us the outlines of an earlier report by the website CRN that it has jettisoned plans for a second-generation version of its Omni-Path interconnect... Read more…

By Staff report

Crystal Ball Gazing: IBM’s Vision for the Future of Computing

October 14, 2019

Dario Gil, IBM’s relatively new director of research, painted a intriguing portrait of the future of computing along with a rough idea of how IBM thinks we’ Read more…

By John Russell

Kubernetes, Containers and HPC

September 19, 2019

Software containers and Kubernetes are important tools for building, deploying, running and managing modern enterprise applications at scale and delivering enterprise software faster and more reliably to the end user — while using resources more efficiently and reducing costs. Read more…

By Daniel Gruber, Burak Yenier and Wolfgang Gentzsch, UberCloud

Intel Debuts Pohoiki Beach, Its 8M Neuron Neuromorphic Development System

July 17, 2019

Neuromorphic computing has received less fanfare of late than quantum computing whose mystery has captured public attention and which seems to have generated mo Read more…

By John Russell

Rise of NIH’s Biowulf Mirrors the Rise of Computational Biology

July 29, 2019

The story of NIH’s supercomputer Biowulf is fascinating, important, and in many ways representative of the transformation of life sciences and biomedical res Read more…

By John Russell

Quantum Bits: Neven’s Law (Who Asked for That), D-Wave’s Steady Push, IBM’s Li-O2- Simulation

July 3, 2019

Quantum computing’s (QC) many-faceted R&D train keeps slogging ahead and recently Japan is taking a leading role. Yesterday D-Wave Systems announced it ha Read more…

By John Russell

With the Help of HPC, Astronomers Prepare to Deflect a Real Asteroid

September 26, 2019

For years, NASA has been running simulations of asteroid impacts to understand the risks (and likelihoods) of asteroids colliding with Earth. Now, NASA and the European Space Agency (ESA) are preparing for the next, crucial step in planetary defense against asteroid impacts: physically deflecting a real asteroid. Read more…

By Oliver Peckham

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This