Numascale Launches Scalable GPU Systems

April 7, 2014

UiO IBMx3755 SystemBased on its innovative interconnect Numascale offers scalable and expandable systems for high performance applications. Adding up standard servers will scale your GPU system within a single image operating system and environment with scalable and shared memory and open for better utilization of the GPUs’ computing power.

Benefits for this solution are easy expansion by standard components and simple operation and programming with shared memory and resources running a single OS.

The standard solution for large GPU systems is to cluster hosts with a limited number of GPUs with Ethernet or Infiniband technology. As in all clusters, a complex message passing software paradigm has to be used and the cluster suffers from nodes with limited size. Individual copies of the OS for each server complicate the operation. Another way is to mount the GPUs in large PCIe systems in high-end servers or in separate cabinets. This solution easily hits scalability limitations imposed by the bus system or server communication.

Based on its unique NumaConnect technology Numascale offers a scalable and expandable solution. Adding up standard servers will scale your GPU system within a single image operating system environment with scalable shared memory.

 

 

IBM System

Numascale offers systems based on two server lines, both with unique advantages. The IBM x3755 M3 server can take up to three AMD 6300 series CPUs, 192 GBytes main memory and a single slot GPU. The IBM server offers many reliability features and configuration flexibility.

AIC 1Uand 2U GPU

Two alternative solutions are based on servers from AIC in 1U and 2U rack mount servers. The 1U server can take one single slot GPU and the 2U server can take two high-end double slot GPUs. Both solutions can be configured with up to 96 GBytes main memory with one AMD 4300 series CPU per node.

Multiple servers are interconnected with NumaConnect to form one scalable monolithic system where all processors can reach all memory and GPU resources directly from the application.

The number of GPUs in a system is limited depending on the type of GPU selected. A system can be configured with more servers than the ones holding the GPUs to form systems with virtually unlimited core count and memory size.

Einar Rustad, CTO in Numascale said: “Our solution shows an easier way of handling larger GPU clusters, control from one OS eases the programming and control of the system considerably and there is potential for getting extreme application performance scaling.”

The big differentiator for NumaConnect compared to other high-speed interconnect technologies is the shared memory and cache coherency mechanisms. These features allow programs to access any memory location and any memory mapped I/O device, like a GPU, in a multiprocessor system with high degree of efficiency. It provides scalable systems with a unified programming model that stays the same from the small multi-core machines used in laptops and desktops to the largest imaginable single system image machines that may contain thousands of processors. NumaConnect also supports low latency MPI.

System administration relates to a unified system as opposed to a large number of separate images in a cluster – less effort to maintain.

Resources can be mapped and used by any processor in the system – optimal use of resources in a standard OS environment.

Process scheduling is synchronized through a single, real-time clock – avoids serialization of scheduling associated with asynchronous operating systems in a cluster and the corresponding loss of efficiency.

About Numascale

With offices in Europe, Asia, and USA, Numascale’s groundbreaking NumaConnect interconnect technology enables scalable server computer systems to be built at cluster prices. NumaConnect allows high-volume manufactured server boards to be used as building blocks for systems with features that are only found in the high-end enterprise servers. NumaConnect includes full support for virtualization of processing, memory, and I/O resources, and can be used with standard operating systems.

Numascale is supported by: Statoil, ProVenture, Investinor, Innovation Norway, Norges forskningsråd, and Eurostars.

Contact: Einar Rustad, CTO Numascale er@numascale.com or your local sales rep.

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!

Nvidia Shares Recipe to Accelerate AI Cloud Adoption

May 29, 2017

In March, Nvidia revealed blueprints for a new open source Tesla GPU-based accelerator – HGX-1 – developed for clouds with Microsoft under its Project Olym Read more…

By Tiffany Trader

Doug Kothe on the Race to Build Exascale Applications

May 29, 2017

Ensuring there are applications ready to churn out useful science when the first U.S. exascale computers arrive in the 2021-2023 timeframe is Doug Kothe’s job Read more…

By John Russell

PRACEdays Reflects Europe’s HPC Commitment

May 25, 2017

More than 250 attendees and participants came together for PRACEdays17 in Barcelona last week, part of the European HPC Summit Week 2017, held May 15-19 at t Read more…

By Tiffany Trader

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurr Read more…

By Doug Black

HPE Extreme Performance Solutions

Exploring the Three Models of Remote Visualization

The explosion of data and advancement of digital technologies are dramatically changing the way many companies do business. With the help of high performance computing (HPC) solutions and data analytics platforms, manufacturers are developing products faster, healthcare providers are improving patient care, and energy companies are improving planning, exploration, and production. Read more…

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

Nvidia CEO Predicts AI ‘Cambrian Explosion’

May 25, 2017

The processing power and cloud access to developer tools used to train machine-learning models are making artificial intelligence ubiquitous across computing pl Read more…

By George Leopold

PGAS Use will Rise on New H/W Trends, Says Reinders

May 25, 2017

If you have not already tried using PGAS, it is time to consider adding PGAS to the programming techniques you know. Partitioned Global Array Space, commonly kn Read more…

By James Reinders

Exascale Escapes 2018 Budget Axe; Rest of Science Suffers

May 23, 2017

President Trump's proposed $4.1 trillion FY 2018 budget is good for U.S. exascale computing development, but grim for the rest of science and technology spend Read more…

By Tiffany Trader

Nvidia Shares Recipe to Accelerate AI Cloud Adoption

May 29, 2017

In March, Nvidia revealed blueprints for a new open source Tesla GPU-based accelerator – HGX-1 – developed for clouds with Microsoft under its Project Olym Read more…

By Tiffany Trader

Doug Kothe on the Race to Build Exascale Applications

May 29, 2017

Ensuring there are applications ready to churn out useful science when the first U.S. exascale computers arrive in the 2021-2023 timeframe is Doug Kothe’s job Read more…

By John Russell

PRACEdays Reflects Europe’s HPC Commitment

May 25, 2017

More than 250 attendees and participants came together for PRACEdays17 in Barcelona last week, part of the European HPC Summit Week 2017, held May 15-19 at t Read more…

By Tiffany Trader

PGAS Use will Rise on New H/W Trends, Says Reinders

May 25, 2017

If you have not already tried using PGAS, it is time to consider adding PGAS to the programming techniques you know. Partitioned Global Array Space, commonly kn Read more…

By James Reinders

Exascale Escapes 2018 Budget Axe; Rest of Science Suffers

May 23, 2017

President Trump's proposed $4.1 trillion FY 2018 budget is good for U.S. exascale computing development, but grim for the rest of science and technology spend Read more…

By Tiffany Trader

Cray Offers Supercomputing as a Service, Targets Biotechs First

May 16, 2017

Leading supercomputer vendor Cray and datacenter/cloud provider the Markley Group today announced plans to jointly deliver supercomputing as a service. The init Read more…

By John Russell

HPE’s Memory-centric The Machine Coming into View, Opens ARMs to 3rd-party Developers

May 16, 2017

Announced three years ago, HPE’s The Machine is said to be the largest R&D program in the venerable company’s history, one that could be progressing tow Read more…

By Doug Black

What’s Up with Hyperion as It Transitions From IDC?

May 15, 2017

If you’re wondering what’s happening with Hyperion Research – formerly the IDC HPC group – apparently you are not alone, says Steve Conway, now senior V Read more…

By John Russell

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Just how close real-wo Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the cam Read more…

By John Russell

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference Read more…

By Tiffany Trader

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its a Read more…

By Tiffany Trader

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

Since our first formal product releases of OSPRay and OpenSWR libraries in 2016, CPU-based Software Defined Visualization (SDVis) has achieved wide-spread adopt Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Last week, Google reported that its custom ASIC Tensor Processing Unit (TPU) was 15-30x faster for inferencing workloads than Nvidia's K80 GPU (see our coverage Read more…

By Tiffany Trader

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a ne Read more…

By Tiffany Trader

Leading Solution Providers

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which w Read more…

By Tiffany Trader

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling Read more…

By Steve Campbell

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Eng Read more…

By Tiffany Trader

US Supercomputing Leaders Tackle the China Question

March 15, 2017

As China continues to prove its supercomputing mettle via the Top500 list and the forward march of its ambitious plans to stand up an exascale machine by 2020, Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu's Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural networ Read more…

By Tiffany Trader

DOE Supercomputer Achieves Record 45-Qubit Quantum Simulation

April 13, 2017

In order to simulate larger and larger quantum systems and usher in an age of "quantum supremacy," researchers are stretching the limits of today's most advance Read more…

By Tiffany Trader

Knights Landing Processor with Omni-Path Makes Cloud Debut

April 18, 2017

HPC cloud specialist Rescale is partnering with Intel and HPC resource provider R Systems to offer first-ever cloud access to Xeon Phi "Knights Landing" process Read more…

By Tiffany Trader

  • arrow
  • Click Here for More Headlines
  • arrow
Share This