The Week in HPC Research

By Tiffany Trader

March 21, 2013

The top research stories of the week have been hand-selected from leading scientific centers, prominent journals and relevant conference proceedings. Here’s another diverse set of items, including an evaluation of sparse matrix multiplication performance on Xeon Phi versus four other architectures; a survey of HPC energy efficiency; performance modeling of OpenMP, MPI and hybrid scientific applications using weak scaling; an exploration of anywhere, anytime cluster monitoring; and a framework for data-intensive cloud storage.

Evaluating Sparse Matrix Multiplication Kernels on Intel Xeon Phi

The Intel Xeon Phi made a big splash at SC12, and computer scientists are eager to put the coprocessor through its paces. Such is the case with a team of researchers from the Ohio State University, who authored a recent paper, describing their work evaluating sparse matrix multiplication kernels on the Intel Xeon Phi.

As the team notes, the Phi sports 61 cores, each supporting 4 hardware threads with 512-bit wide SIMD registers for a theoretical peak performance of 1 teraflops double precision.

Their paper is meant to serve as an introduction to the Phi architecture and to analyze its peak performance using the sparse matrix as a test application. It’s a good choice to test the Phi’s capabilities because it is representative of many large-scale applications and because it is a difficult problem for coprocessor architectures.

As the team writes: “Many scientific applications involve operations on large sparse matrices such as linear solvers, eigensolver, and graph mining algorithms. The core of most of these applications involves the multiplication of a large, sparse matrix with a dense vector (SpMV).”

They also note that “the irregularity and sparsity of SpMV-like kernels create several problems for these architectures [i.e. accelerators/coprocessors].”

The researchers compared the sparse matrix multiplication performance of Xeon Phi with four other architectures: two dual Intel Xeon processors, X5680 (Westmere) and E5-2670 (Sandy Bridge), as well as two NVIDIA Tesla GPUs C2050 and K20. They results of their experiment show that the Phi offered superior performance.

They write that “although the design of a Xeon Phi core is not much different than those of the cores in modern processors, its large number of cores and hyperthreading capability allow many application to saturate the available memory bandwidth, which is not the case for many cutting-edge processors. Yet, our performance studies show that it is the memory latency not the bandwidth which creates a bottleneck for SpMV on this architecture. Finally, our experiments show that Xeon Phi’s sparse kernel performance is very promising and even better than that of cutting-edge general purpose processors and GPUs.”

Next >>

Energy Awareness in HPC: A Survey

A group of researchers from the Walchand College of Engineering, in the city of Sangli, Maharashtra, India, have published a paper addressing one of the most pressing problems in high-performance computing: energy-efficiency.

The team sets out by acknowledging the increased awareness of energy and costs associated with power management for high performance computing. They write that “power control is becoming a key challenge for effectively operating a modern high end computing infrastructures such as server, clusters, data centers and grids,” although the scope of the paper is primarily concerned with cluster systems.

The researchers argue that developing energy efficient computer designs is the next major goal of the high performance computing. The paper presents a survey and classification of energy efficient techniques for cluster computing. The research outlines both hardware and software related variables and sub-classes thereof. An important point made in the paper is that performance itself does not become a secondary objective but it is understood that power is a constraint to increasing performance.

Next >>

Performance Modeling of Hybrid MPI/OpenMP Applications at Scale

Texas A&M University computer scientists Xingfu Wu and Valerie Taylor are exploring a performance modeling framework based on memory bandwidth contention time and a parameterized communication model. They have co-authored a paper describing their work with modeling and predicting the performance of OpenMP, MPI and hybrid scientific applications using weak scaling on large-scale multicore supercomputers.


The research team employed STREAM memory benchmarks to identify initial performance and model validation of MPI and OpenMP applications. They also used the hybrid large-scale scientific application Gyrokinetic Toroidal Code in magnetic fusion to validate the performance model.

The experiment used three different supercomputers: an IBM POWER4, POWER5+ and BlueGene/P. Study results showed an error rate of less than 7.77% for predicting the performance of hybrid MPI/OpenMP GTC on up to 512 cores on these multicore systems.

Next >>

Anywhere Anytime Cluster Monitoring

A trio of computer scientists from Shandong University in Jinan, China, are exploring the feasibility of anywhere, anytime cluster monitoring. More specifically, they are working to design and implement a cluster monitoring system based on Android.

The team starts with the view that high performance computing (HPC) has been democratized to the point that HPC clusters have become an important resource for many scientific fields, including graphics, biology, physics, climate research, and many others. Still, depending on local funding realities, the availability of such machines is almost universally constrained. In light of this, monitoring becomes an essential task necessary for the efficient utilization and management of limited resources. However, as the researchers observe, traditional cluster monitoring systems demonstrate poor mobility, which stymies proper management.

The authors are seeking to improve the flexibility of monitoring systems and improve the communication between administrators. They assert that the mobile cluster monitoring system outlined in their paper “will make it possible to monitor the whole cluster anywhere and anytime to allow administrators to manage, diagnose, and troubleshoot cluster issues more accurately and promptly.”

The system they developed is based on the Android platform, the brainchild of Google, and built on open source monitoring tools, Gaglia and Nagios. The design uses a client-server model, where the server probes the data via monitoring tools and produces a global view of the data. The mobile client gets the monitoring packages by Socket. Then, the cluster’s status is displayed on the Android application.

Their work was published as a chapter in the book, Pervasive Computing and the Networked World.

Next >>

A Framework for Cloud Storage

UK computer scientists Victor Chang, Robert John Walters and Gary Wills set out to explore the topic of cloud storage and bioinformatics in a private cloud deployment. They’ve written a paper about their experience to serve as a resource for other researchers with data-intensive compute needs who are interested in analyzing the benefits of a cloud model.

Among the many benefits of the cloud model are its cost-savings potential, agility, efficiency, resource consolidation, business opportunities and possible energy savings. Despite the inherent attractiveness, there are still barriers to overcome, and one of these, according to the authors is the need for a standard or framework to manage both operations and IT services.

They write that “this framework needs to provide the structure necessary to ensure any cloud implementation meets the business needs of industry and academia and include recommendations of best practices which can be adapted for different domains and platforms.”

Their work examines service portability for a private cloud deployment. Storage, backup and data migration and data recovery are all addressed. The paper presents a detailed case study about cloud storage and bioinformatics services developed as part of the Cloud Computing Adoption Framework (CCAF). In order to illustrate the benefits of CCAF the authors provide several bioinformatics examples, including tumor modeling, brain imaging, insulin molecules and simulations for medical training. They believe that their proposed solution offers cost reduction, time-savings and user friendliness.

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!

Pfizer HPC Engineer Aims to Automate Software Stack Testing

January 17, 2019

Seeking to reign in the tediousness of manual software testing, Pfizer HPC Engineer Shahzeb Siddiqui is developing an open source software tool called buildtest, aimed at automating software stack testing by providing the community with a central repository of tests for common HPC apps and the ability to automate execution of testing. Read more…

By Tiffany Trader

Senegal Prepares to Take Delivery of Atos Supercomputer

January 16, 2019

In just a few months time, Senegal will be operating the second largest HPC system in sub-Saharan Africa. The Minister of Higher Education, Research and Innovation Mary Teuw Niane made the announcement on Monday (Jan. 14 Read more…

By Tiffany Trader

Google Cloud Platform Extends GPU Instance Options

January 16, 2019

If it's Nvidia GPUs you're after to power your AI/HPC/visualization workload, Google Cloud has them, now claiming "broadest GPU availability." Each of the three big public cloud vendors has by turn touted the latest and Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

HPE Systems With Intel Omni-Path: Architected for Value and Accessible High-Performance Computing

Today’s high-performance computing (HPC) and artificial intelligence (AI) users value high performing clusters. And the higher the performance that their system can deliver, the better. Read more…

IBM Accelerated Insights

Resource Management in the Age of Artificial Intelligence

New challenges demand fresh approaches

Fueled by GPUs, big data, and rapid advances in software, the AI revolution is upon us. Read more…

STAC Floats ML Benchmark for Financial Services Workloads

January 16, 2019

STAC (Securities Technology Analysis Center) recently released an ‘exploratory’ benchmark for machine learning which it hopes will evolve into a firm benchmark or suite of benchmarking tools to compare the performanc Read more…

By John Russell

Google Cloud Platform Extends GPU Instance Options

January 16, 2019

If it's Nvidia GPUs you're after to power your AI/HPC/visualization workload, Google Cloud has them, now claiming "broadest GPU availability." Each of the three Read more…

By Tiffany Trader

STAC Floats ML Benchmark for Financial Services Workloads

January 16, 2019

STAC (Securities Technology Analysis Center) recently released an ‘exploratory’ benchmark for machine learning which it hopes will evolve into a firm benchm Read more…

By John Russell

A Big Data Journey While Seeking to Catalog our Universe

January 16, 2019

It turns out, astronomers have lots of photos of the sky but seek knowledge about what the photos mean. Sound familiar? Big data problems are often characterize Read more…

By James Reinders

Intel Bets Big on 2-Track Quantum Strategy

January 15, 2019

Quantum computing has lived so long in the future it’s taken on a futuristic life of its own, with a Gartner-style hype cycle that includes triggers of innovation, inflated expectations and – though a useful quantum system is still years away – anticipatory troughs of disillusionment. Read more…

By Doug Black

IBM Quantum Update: Q System One Launch, New Collaborators, and QC Center Plans

January 10, 2019

IBM made three significant quantum computing announcements at CES this week. One was introduction of IBM Q System One; it’s really the integration of IBM’s Read more…

By John Russell

IBM’s New Global Weather Forecasting System Runs on GPUs

January 9, 2019

Anyone who has checked a forecast to decide whether or not to pack an umbrella knows that weather prediction can be a mercurial endeavor. It is a Herculean task: the constant modeling of incredibly complex systems to a high degree of accuracy at a local level within very short spans of time. Read more…

By Oliver Peckham

The Case Against ‘The Case Against Quantum Computing’

January 9, 2019

It’s not easy to be a physicist. Richard Feynman (basically the Jimi Hendrix of physicists) once said: “The first principle is that you must not fool yourse Read more…

By Ben Criger

The Deep500 – Researchers Tackle an HPC Benchmark for Deep Learning

January 7, 2019

How do you know if an HPC system, particularly a larger-scale system, is well-suited for deep learning workloads? Today, that’s not an easy question to answer Read more…

By John Russell

Quantum Computing Will Never Work

November 27, 2018

Amid the gush of money and enthusiastic predictions being thrown at quantum computing comes a proposed cold shower in the form of an essay by physicist Mikhail Read more…

By John Russell

Cray Unveils Shasta, Lands NERSC-9 Contract

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. Read more…

By Tiffany Trader

AMD Sets Up for Epyc Epoch

November 16, 2018

It’s been a good two weeks, AMD’s Gary Silcott and Andy Parma told me on the last day of SC18 in Dallas at the restaurant where we met to discuss their show news and recent successes. Heck, it’s been a good year. Read more…

By Tiffany Trader

The Case Against ‘The Case Against Quantum Computing’

January 9, 2019

It’s not easy to be a physicist. Richard Feynman (basically the Jimi Hendrix of physicists) once said: “The first principle is that you must not fool yourse Read more…

By Ben Criger

US Leads Supercomputing with #1, #2 Systems & Petascale Arm

November 12, 2018

The 31st Supercomputing Conference (SC) - commemorating 30 years since the first Supercomputing in 1988 - kicked off in Dallas yesterday, taking over the Kay Ba Read more…

By Tiffany Trader

Contract Signed for New Finnish Supercomputer

December 13, 2018

After the official contract signing yesterday, configuration details were made public for the new BullSequana system that the Finnish IT Center for Science (CSC Read more…

By Tiffany Trader

Nvidia’s Jensen Huang Delivers Vision for the New HPC

November 14, 2018

For nearly two hours on Monday at SC18, Jensen Huang, CEO of Nvidia, presented his expansive view of the future of HPC (and computing in general) as only he can do. Animated. Backstopped by a stream of data charts, product photos, and even a beautiful image of supernovae... Read more…

By John Russell

HPE No. 1, IBM Surges, in ‘Bucking Bronco’ High Performance Server Market

September 27, 2018

Riding healthy U.S. and global economies, strong demand for AI-capable hardware and other tailwind trends, the high performance computing server market jumped 28 percent in the second quarter 2018 to $3.7 billion, up from $2.9 billion for the same period last year, according to industry analyst firm Hyperion Research. Read more…

By Doug Black

Leading Solution Providers

SC 18 Virtual Booth Video Tour

Advania @ SC18 AMD @ SC18
ASRock Rack @ SC18
DDN Storage @ SC18
HPE @ SC18
IBM @ SC18
Lenovo @ SC18 Mellanox Technologies @ SC18
NVIDIA @ SC18
One Stop Systems @ SC18
Oracle @ SC18 Panasas @ SC18
Supermicro @ SC18 SUSE @ SC18 TYAN @ SC18
Verne Global @ SC18

Summit Supercomputer is Already Making its Mark on Science

September 20, 2018

Summit, now the fastest supercomputer in the world, is quickly making its mark in science – five of the six finalists just announced for the prestigious 2018 Read more…

By John Russell

HPC Reflections and (Mostly Hopeful) Predictions

December 19, 2018

So much ‘spaghetti’ gets tossed on walls by the technology community (vendors and researchers) to see what sticks that it is often difficult to peer through Read more…

By John Russell

Intel Confirms 48-Core Cascade Lake-AP for 2019

November 4, 2018

As part of the run-up to SC18, taking place in Dallas next week (Nov. 11-16), Intel is doling out info on its next-gen Cascade Lake family of Xeon processors, specifically the “Advanced Processor” version (Cascade Lake-AP), architected for high-performance computing, artificial intelligence and infrastructure-as-a-service workloads. Read more…

By Tiffany Trader

Germany Celebrates Launch of Two Fastest Supercomputers

September 26, 2018

The new high-performance computer SuperMUC-NG at the Leibniz Supercomputing Center (LRZ) in Garching is the fastest computer in Germany and one of the fastest i Read more…

By Tiffany Trader

Houston to Field Massive, ‘Geophysically Configured’ Cloud Supercomputer

October 11, 2018

Based on some news stories out today, one might get the impression that the next system to crack number one on the Top500 would be an industrial oil and gas mon Read more…

By Tiffany Trader

Microsoft to Buy Mellanox?

December 20, 2018

Networking equipment powerhouse Mellanox could be an acquisition target by Microsoft, according to a published report in an Israeli financial publication. Microsoft has reportedly gone so far as to engage Goldman Sachs to handle negotiations with Mellanox. Read more…

By Doug Black

The Deep500 – Researchers Tackle an HPC Benchmark for Deep Learning

January 7, 2019

How do you know if an HPC system, particularly a larger-scale system, is well-suited for deep learning workloads? Today, that’s not an easy question to answer Read more…

By John Russell

House Passes $1.275B National Quantum Initiative

September 17, 2018

Last Thursday the U.S. House of Representatives passed the National Quantum Initiative Act (NQIA) intended to accelerate quantum computing research and developm Read more…

By John Russell

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