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!

Researchers Use Supercomputing to Study Links Between Hurricanes and Climate Change

July 19, 2019

As climate change looms, researchers are scrambling to answer the question of how a warming planet will affect the frequency and severity of already-deadly hurricanes. Now, a team of researchers from the University of Il Read more…

By Oliver Peckham

San Diego Supercomputer Center to Welcome ‘Expanse’ Supercomputer in 2020

July 18, 2019

With a $10 million dollar award from the National Science Foundation, San Diego Supercomputer Center (SDSC) at the University of California San Diego is procuring a new supercomputer, called Expanse, to be deployed next Read more…

By Staff report

Informing Designs of Safer, More Efficient Aircraft with Exascale Computing

July 18, 2019

During the process of designing an aircraft, aeronautical engineers must perform predictive simulations to understand how airflow around the plane impacts flight characteristics. However, modeling the complexities and su Read more…

By Rob Johnson

HPE Extreme Performance Solutions

Bring the Combined Power of HPC and AI to Your Business Transformation

A growing number of commercial businesses are implementing HPC solutions to derive actionable business insights, to run higher performance applications and to gain a competitive advantage. Read more…

IBM Accelerated Insights

Smarter Technology Revs Up Red Bull Racing

In 21st century business, companies that effectively leverage their information resources – thrive. As it turns out, the same is true in Formula One racing. Read more…

How Fast is Your Rubik Solver; This One’s Probably Faster

July 18, 2019

In the race to solve Rubik’s Cube, the time-to-finish keeps shrinking. This year Philipp Weyer from Germany won the 10th World Cube Association (WCA) Championship held in Melbourne, Australia, with a 6.74-second perfo Read more…

By John Russell

Informing Designs of Safer, More Efficient Aircraft with Exascale Computing

July 18, 2019

During the process of designing an aircraft, aeronautical engineers must perform predictive simulations to understand how airflow around the plane impacts fligh Read more…

By Rob Johnson

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

Goonhilly Unveils New Immersion-Cooled Platform, Doubles Down on Sustainability Mission

July 16, 2019

Goonhilly Earth Station has opened its new datacenter – an enhancement to its existing tier 3 facility – in Cornwall, England, touting an ambitious commitme Read more…

By Oliver Peckham

ISC19 Cluster Competition: Application Results, Finally!

July 15, 2019

Our exhaustive coverage of the ISC19 Student Cluster Competition continues as we discuss the application scores below. While the scores were typically high, som Read more…

By Dan Olds

Nvidia Expands DGX-Ready AI Program to 19 Countries

July 11, 2019

Nvidia’s DGX-Ready Data Center Program, announced in January and designed to provide colo and public cloud-like options to access the company’s GPU-powered Read more…

By Doug Black

Argonne Team Makes Record Globus File Transfer

July 10, 2019

A team of scientists at Argonne National Laboratory has broken a data transfer record by moving a staggering 2.9 petabytes of data for a research project.  The data – from three large cosmological simulations – was generated and stored on the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF)... Read more…

By Oliver Peckham

Nvidia, Google Tie in Second MLPerf Training ‘At-Scale’ Round

July 10, 2019

Results for the second round of the AI benchmarking suite known as MLPerf were published today with Google Cloud and Nvidia each picking up three wins in the at Read more…

By Tiffany Trader

Applied Materials Embedding New Memory Technologies in Chips

July 9, 2019

Applied Materials, the $17 billion Santa Clara-based materials engineering company for the semiconductor industry, today announced manufacturing systems enablin Read more…

By Doug Black

High Performance (Potato) Chips

May 5, 2006

In this article, we focus on how Procter & Gamble is using high performance computing to create some common, everyday supermarket products. Tom Lange, a 27-year veteran of the company, tells us how P&G models products, processes and production systems for the betterment of consumer package goods. Read more…

By Michael Feldman

Cray, AMD to Extend DOE’s Exascale Frontier

May 7, 2019

Cray and AMD are coming back to Oak Ridge National Laboratory to partner on the world’s largest and most expensive supercomputer. The Department of Energy’s Read more…

By Tiffany Trader

Graphene Surprises Again, This Time for Quantum Computing

May 8, 2019

Graphene is fascinating stuff with promise for use in a seeming endless number of applications. This month researchers from the University of Vienna and Institu Read more…

By John Russell

AMD Verifies Its Largest 7nm Chip Design in Ten Hours

June 5, 2019

AMD announced last week that its engineers had successfully executed the first physical verification of its largest 7nm chip design – in just ten hours. The AMD Radeon Instinct Vega20 – which boasts 13.2 billion transistors – was tested using a TSMC-certified Calibre nmDRC software platform from Mentor. Read more…

By Oliver Peckham

TSMC and Samsung Moving to 5nm; Whither Moore’s Law?

June 12, 2019

With reports that Taiwan Semiconductor Manufacturing Co. (TMSC) and Samsung are moving quickly to 5nm manufacturing, it’s a good time to again ponder whither goes the venerable Moore’s law. Shrinking feature size has of course been the primary hallmark of achieving Moore’s law... Read more…

By John Russell

Deep Learning Competitors Stalk Nvidia

May 14, 2019

There is no shortage of processing architectures emerging to accelerate deep learning workloads, with two more options emerging this week to challenge GPU leader Nvidia. First, Intel researchers claimed a new deep learning record for image classification on the ResNet-50 convolutional neural network. Separately, Israeli AI chip startup Hailo.ai... Read more…

By George Leopold

Nvidia Embraces Arm, Declares Intent to Accelerate All CPU Architectures

June 17, 2019

As the Top500 list was being announced at ISC in Frankfurt today with an upgraded petascale Arm supercomputer in the top third of the list, Nvidia announced its Read more…

By Tiffany Trader

Top500 Purely Petaflops; US Maintains Performance Lead

June 17, 2019

With the kick-off of the International Supercomputing Conference (ISC) in Frankfurt this morning, the 53rd Top500 list made its debut, and this one's for petafl 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

Intel Launches Cascade Lake Xeons with Up to 56 Cores

April 2, 2019

At Intel's Data-Centric Innovation Day in San Francisco (April 2), the company unveiled its second-generation Xeon Scalable (Cascade Lake) family and debuted it Read more…

By Tiffany Trader

Cray – and the Cray Brand – to Be Positioned at Tip of HPE’s HPC Spear

May 22, 2019

More so than with most acquisitions of this kind, HPE’s purchase of Cray for $1.3 billion, announced last week, seems to have elements of that overused, often Read more…

By Doug Black and Tiffany Trader

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

Announcing four new HPC capabilities in Google Cloud Platform

April 15, 2019

When you’re running compute-bound or memory-bound applications for high performance computing or large, data-dependent machine learning training workloads on Read more…

By Wyatt Gorman, HPC Specialist, Google Cloud; Brad Calder, VP of Engineering, Google Cloud; Bart Sano, VP of Platforms, Google Cloud

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

In Wake of Nvidia-Mellanox: Xilinx to Acquire Solarflare

April 25, 2019

With echoes of Nvidia’s recent acquisition of Mellanox, FPGA maker Xilinx has announced a definitive agreement to acquire Solarflare Communications, provider Read more…

By Doug Black

Qualcomm Invests in RISC-V Startup SiFive

June 7, 2019

Investors are zeroing in on the open standard RISC-V instruction set architecture and the processor intellectual property being developed by a batch of high-flying chip startups. Last fall, Esperanto Technologies announced a $58 million funding round. Read more…

By George Leopold

Nvidia Claims 6000x Speed-Up for Stock Trading Backtest Benchmark

May 13, 2019

A stock trading backtesting algorithm used by hedge funds to simulate trading variants has received a massive, GPU-based performance boost, according to Nvidia, Read more…

By Doug Black

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