The Week in HPC Research

By Nicole Hemsoth

February 21, 2013

The top research stories of the week have been hand-selected from prominent journals and leading conference proceedings. Here’s another diverse set of items, including one on GPU programming, distributed file systems, exhaustive search with parallel agents, the benefits of invasive computing, and an HPC cloud proof-of-concept.

Extending OpenMP for GPU Programming

The International Journal of Computational Science and Engineering (Volume 8, Number 1/2013) includes an interesting research item from Seyong Lee (Computer Science and Mathematics Division, Oak Ridge National Laboratory) and Rudolf Eigenmann (School of Electrical and Computer Engineering, Purdue University). The duo have developed a directive-based OpenMP extension to address programmability and tunability issues relevant to the GPGPU developer community.

GPGPU computing provides an inexpensive parallel computing platform for compute-intensive applications, yet programming complexity can challenge developers hindering more widespread adoption, the authors note. “Even though the compute unified device architecture (CUDA) programming model offers better abstraction, developing efficient GPGPU code is still complex and error–prone,” they argue.

Thus the authors propose a new programming interface, called OpenMPC, comprised of standard OpenMP and a new set of compiler directives and environment variables that have been extended for CUDA. They argue that OpenMPC, a directive–based, high–level programming model, offers better programmability and tunability for GPGPU code.

“We have developed a fully automatic compilation and user–assisted tuning system supporting OpenMPC. In addition to a range of compiler transformations and optimisations, the system includes tuning capabilities for generating, pruning, and navigating the search space of compilation variants. Evaluation using 14 applications shows that our system achieves 75% of the performance of the hand–coded CUDA programmes (92% if excluding one exceptional case),” they write.

Next >>

Six Distributed File Systems

A trio of French scientists provide a thorough analysis of six distributed file systems in this recent 39-page research paper, appearing in the HAL/INRIA open archive. The authors, one from SysFera and two from Laboratoire MIS at the Universite de Picardie Jules Verne, start with the observation that a large number of HPC applications rely on distributed computing environments to process and analyze large amounts of data. (Examples provided include probabilistic analysis, weather forecasting and aerodynamic research.) They further note the emergence of new infrastructures designed to handle the increased computational demand. Most of these new architectures, the authors assert, involve some manner of distributed computing, such that the computing process is spread among the nodes of a large distributed computing platform.

Furthermore the team believes that the growing body of scientific data will likewise necessitate innovations in distributed storage. “Easy to use and reliable storage solutions” are essential for scientific computing, they argue, and the community already has a “well-tried solution to this issue,” in the form of Distributed File Systems (DFSs).

The paper offers a comparison of six modern DFSs as to three fundamental issues: scalability, transparency and fault tolerance. For their study, the authors selected popular, widely-used and frequently updated DFSs: HDFS, MooseFS, iRODS, Ceph, GlusterFS, and Lustre.

Next >>

Exhaustive Search with Parallel Agents

In a recent paper, Macedonia researcher Toni Draganov Stojanovski from University for Information Science And Technology in the Republic of Macedonia sets out to examine the performance of exhaustive search when it is conducted with many search agents working in parallel.

Stojanovski and his research team observe that the advance of manycore processors and more sophisticated distributed processing offers more opportunities for exhaustive search via the use of multiple search agents. While there are a selection of elegant algorithms available for solving complex problems, exhaustive search remains as the best or only solution for real-life problems with no regular structure.

The paper reviews the performance that is achieved using the exhaustive search approach in conjunction with several different search agents with special attention to the following parameters:

• Differences in speeds of search agents.

• Length of allocated search subregions.

• Type of communication between central server and agents.

The findings reveal that the performance of the search improves with the increase in the level of mutual assistance between agents. Furthermore, nearly identical performance outcomes can be achieved with homogeneous and heterogeneous search agents as long as “the lengths of subregions allocated to individual search regions follow the differences in the speeds of heterogeneous search agents.” The research team also demonstrate how to achieve the optimum search performance by means of increasing the dimension of the search region.

The work appears in the January issue of the Turkish Journal of Electrical Engineering & Computer Sciences.

Next >>

The Benefits of Invasive Computing

In their paper, titled Invasive Computing on High Performance Shared Memory Systems, three researchers from the Department of Informatics, at Garching, Germany, offer new approaches for improving the throughput of runtime-adaptive applications on cutting-edge HPC systems. Their work was published as a chapter in Facing the Multicore Challenge III.

According to the team, there are multiple issues at play:

A first issue is the, in general, missing information about the actual impact of unforeseeable workload by adaptivity and of the unknown number of time steps or iterations on the runtime of adaptive applications. Another issue is that resource scheduling on HPC systems is currently done before an application is started and remains unchanged afterwards, even in case of varying requirements. Furthermore, an application cannot be started after another running application allocated all resources.

The authors propose a solution that involves the design of algorithms that adapt their use of resources during runtime, e.g., by relinquishing or adding compute cores. In the event that concurrent applications are competing for resources, they recommend that an appropriate resource management solution be adopted.

To improve the throughput of runtime-adaptive applications, the computer scientists employed invasive paradigms that start applications and schedule resources during runtime. Scheduling work can be achieved through the use of a global resource manager, and scalability graphs help improve load balancing of multiple applications. In the case of adaptive simulations, several scalability graphs are employed.

The paper includes a proof-of-concept that demonstrates runtime/throughput results for a fully adaptive shallow-water simulation.

Next >>

Easy to Use Cloud Service

Among the many HPC cloud research pieces that were published this week was an Australian endeavor that seeks to transform complicated HPC applications into easy-to-use SaaS cloud services. Researchers Adam K.L. Wonga and Andrzej M. Goscinskia from the School of Information Technology at Deakin University in Australia set out to develop and test a unified framework for HPC applications as services in clouds.

The duo acknowledge the benefits of HPC cloud. Scalable, affordable and accessible on demand, the use of HPC resources in a cloud environment have been a natural fit for many scientific disciplines, including biology, medicine, chemistry, they write. Still they have observed a steep learning curve when it comes to preparing for and deploying HPC applications in the cloud. This they say has stood in the way of many innovative HPC-backed discoveries.

To remedy this situation and improve ease of use and access to HPC resources, the researchers are looking to the world of Web-based tools, but as they write “high-performance computational research are both unique and complex, which make the development of web-based tools for this research difficult.”

The paper describes their approach to developing a unified cloud framework – one that makes it easier for various domain users to deploy HPC applications in public clouds as services. Their proof-of-concept integrates three components:

(i) Amazon EC2 public cloud for providing HPC infrastructure.

(ii) a HPC service software library for accessing HPC resources.

(iii) the Galaxy web-based platform for exposing and accessing HPC application services.

The authors conclude that “this new approach can reduce the time and money needed to deploy, expose and access discipline HPC applications in clouds.”

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!

AI Thought Leaders on Capitol Hill

July 14, 2018

On Thursday, July 12, the House Committee on Science, Space, and Technology heard from four academic and industry leaders – representatives from Berkeley Lab, Argonne Lab, GE Global Research and Carnegie Mellon University – on the opportunities springing from the intersection of machine learning and advanced-scale computing. Read more…

By Tiffany Trader

HPC Serves as a ‘Rosetta Stone’ for the Information Age

July 12, 2018

In an age defined and transformed by its data, several large-scale scientific instruments around the globe might be viewed as a ‘mother lode’ of precious data. With names seemingly created for a ‘techno-speak’ glossary, these interferometers, cyclotrons, sequencers, solenoids, satellite altimeters, and cryo-electron microscopes are churning out data in previously unthinkable and seemingly incomprehensible quantities -- billions, trillions and quadrillions of bits and bytes of electro-magnetic code. Read more…

By Warren Froelich

Can Markov Logic Take Machine Learning to the Next Level?

July 11, 2018

Advances in machine learning, including deep learning, have propelled artificial intelligence (AI) into the public conscience and forced executives to create new business plans based on data. However, the scarcity of hig Read more…

By Alex Woodie

HPE Extreme Performance Solutions

Introducing the First Integrated System Management Software for HPC Clusters from HPE

How do you manage your complex, growing cluster environments? Answer that big challenge with the new HPC cluster management solution: HPE Performance Cluster Manager. Read more…

IBM Accelerated Insights

ORNL Summit Supercomputer Is Officially Here

Oak Ridge National Laboratory (ORNL) together with IBM and Nvidia celebrated the official unveiling of the Department of Energy (DOE) Summit supercomputer today at an event presided over by DOE Secretary Rick Perry. Read more…

CSIR, Nvidia Partner to Launch GPU-Powered AI Center in India

July 10, 2018

As reported by a number of Indian news outlets, India’s Council of Scientific and Industrial Research (CSIR) is partnering with Nvidia to establish a new, AI-focused Centre of Excellence in New Delhi, India's capital. Read more…

By Oliver Peckham

AI Thought Leaders on Capitol Hill

July 14, 2018

On Thursday, July 12, the House Committee on Science, Space, and Technology heard from four academic and industry leaders – representatives from Berkeley Lab, Argonne Lab, GE Global Research and Carnegie Mellon University – on the opportunities springing from the intersection of machine learning and advanced-scale computing. Read more…

By Tiffany Trader

HPC Serves as a ‘Rosetta Stone’ for the Information Age

July 12, 2018

In an age defined and transformed by its data, several large-scale scientific instruments around the globe might be viewed as a ‘mother lode’ of precious data. With names seemingly created for a ‘techno-speak’ glossary, these interferometers, cyclotrons, sequencers, solenoids, satellite altimeters, and cryo-electron microscopes are churning out data in previously unthinkable and seemingly incomprehensible quantities -- billions, trillions and quadrillions of bits and bytes of electro-magnetic code. Read more…

By Warren Froelich

Tsinghua Powers Through ISC18 Field

July 10, 2018

Tsinghua University topped all other competitors at the ISC18 Student Cluster Competition with an overall score of 88.43 out of 100. This gives Tsinghua their s Read more…

By Dan Olds

HPE, EPFL Launch Blue Brain 5 Supercomputer

July 10, 2018

HPE and the Ecole Polytechnique Federale de Lausannne (EPFL) Blue Brain Project yesterday introduced Blue Brain 5, a new supercomputer built by HPE, which displ Read more…

By John Russell

Pumping New Life into HPC Clusters, the Case for Liquid Cooling

July 10, 2018

High Performance Computing (HPC) faces some daunting challenges in the coming years as traditional, industry-standard systems push the boundaries of data center Read more…

By Scott Tease

Meet the ISC18 Cluster Teams: Up Close & Personal

July 6, 2018

It’s time to meet your ISC18 Student Cluster Competition teams. While I was able to film them live at the ISC show, the trick was finding time to edit the vid Read more…

By Dan Olds

PRACEdays18 Keynote Allan Williams (Australia/NCI): We’re Open for Business Down Under!

July 5, 2018

The University of Ljubljana in Slovenia hosted the third annual EHPCSW18 and fifth annual PRACEdays18 events which opened with a plenary session on May 29, 2018 Read more…

By Elizabeth Leake (STEM-Trek for HPCwire)

HPC Under the Covers: Linpack, Exascale & the Top500

June 28, 2018

HPCers can get painted as a monolithic bunch by outsiders, but internecine disagreements abound over the HPCest of HPC jargon, as was evident at ISC this week. Read more…

By Tiffany Trader

Leading Solution Providers

SC17 Booth Video Tours Playlist

Altair @ SC17

Altair

AMD @ SC17

AMD

ASRock Rack @ SC17

ASRock Rack

CEJN @ SC17

CEJN

DDN Storage @ SC17

DDN Storage

Huawei @ SC17

Huawei

IBM @ SC17

IBM

IBM Power Systems @ SC17

IBM Power Systems

Intel @ SC17

Intel

Lenovo @ SC17

Lenovo

Mellanox Technologies @ SC17

Mellanox Technologies

Microsoft @ SC17

Microsoft

Penguin Computing @ SC17

Penguin Computing

Pure Storage @ SC17

Pure Storage

Supericro @ SC17

Supericro

Tyan @ SC17

Tyan

Univa @ SC17

Univa

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