The Week in Research

By HPCwire Staff

March 28, 2013

There are a few themes that run along this week’s pick for the top research items that emerged over the last seven days. Among these are making systems running HPC applications more efficient, both at the VM and storage layers. Further, we present research on energy efficiency, job scheduling and resource sharing.

Without further delay, let’s dive in…

Resetting Resource Priorities

A team of Czech researchers has focused in on an ongoing problem that affects users on shared systems – creating a fair sharing of computational resources.

The researchers note that the as it stands, the user with the smallest CPU needs gets pushed to the front of the line while those with more pressing computational loads get shoved behind. They note that this is inherently unfair as this method “does not reflect other consumed resources like RAM, HDD storage capacity or GPU cores.” In fact, as they note, there is wide variance among users – some who might have heterogeneous needs who are being rated in queue based on CPU time alone.

To address this, they have proposed a new approach to resource sharing that would “allow the development of usable multi-resource-aware user prioritization mechanisms.” They showed how different resources can be weighed and combined in one formula that can reset resource priorities.

The team adds that when it comes to multiple resources, it is not always realistic to expect a completely fair solution, but this approach does take into account the need to move from CPU-only prioritization decisions.

Zapping Energy Costs on IBM Blue Gene/P

A team from the Illinois Institute of Technology and Argonne National Laboratory has explored the greater issues of energy expenses in the overall HPC field, pointing to the variations in electricity prices at different points during the day.

On that note, they propose a “smart, power-aware job scheduling approach for HPC systems based on variable energy price and job power profiles.” At the heart of this is a “0-1 knapsack model” that they say can save on energy costs while also being a flexible and effective way to schedule jobs without degrading system utilization.

To put their theory in practice, they used the approach to design scheduling strategies for the Blue Gene/P using synthetic data and real job traces from production systems. They were able to demonstrate how their power-aware job scheduling approach can reduce energy expenses by up to 25 percent while having only a minimal impact on overall system utilization.

Next – Process Placement in Multicore Clusters >

 

Process Placement in Multicore Clusters

A recent research report from a French team affiliated with Inria discussed how current generations of NUMA node clusters feature multicore processors. They point to how this creates some programming challenges due to the many hardware elements that must be taken into account.

Specifically, they note how with the expected increase of application concurrency and input data size, one of the most important challenges to be addressed in coming years  is that of locality, or how to improve data access and transfer within the application.

To address this, they point to an idea that they say can improve the performance of parallel applications by decreasing their communication costs via matching the communication pattern to the underlying hardware architecture.

They detail the algorithm and techniques behind idea, which involves gathering the communication pattern information and the hardware info. They are then able to compute a relevant reordering of the various process ranks of the application. They use those new ranks to reduce the communication costs of the application.

HPC Clouds – Cloud Storage with OpenStack Swift

A team from Los Alamos National Laboratory has revealed how they used the Swift Object Store from OpenStack as their disk-based cloud storage system. For the team, Swift has provided an “open source software for creating redundant, scalable object storage using clusters of standardized servers to store petabytes of accessible data.”

At the heart of this effort is to address growing HPC requirements on the archiving side. They note that just buying more tape or hard drives to keep up with demand is not a viable solution and they believe that “merging advanced features from both HPC systems and cloud systems is a promising direction.”

They reiterate that this is not a file system or real-time storage approach, but rather a “long term storage system for a more permanent type of static data that can be retrieved, leveraged and then updated if necessary.”

As the team behind the project states,

At LANL, we have worked on high-performance computing (HPC) systems for many years. The LANL parallel log file system (PLFS) has demonstrated its superior capability for the conversion of logical N-to-1 parallel I/O operations into physical N-to-N parallel I/O operations on HPC production systems. In this article, we describe the leveraging of the scaling capability of cloud object storage systems and the transformative parallel I/O feature (Fig. 1) of the LANL PLFS and the building of a parallel cloud storage system.

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!

Is Data Science the Fourth Pillar of the Scientific Method?

April 18, 2019

Nvidia CEO Jensen Huang revived a decade-old debate last month when he said that modern data science (AI plus HPC) has become the fourth pillar of the scientific method. While some disagree with the notion that statistic Read more…

By Alex Woodie

At ASF 2019: The Virtuous Circle of Big Data, AI and HPC

April 18, 2019

We've entered a new phase in IT -- in the world, really -- where the combination of big data, artificial intelligence, and high performance computing is pushing the bounds of what's possible in business and science, in w Read more…

By Alex Woodie with Doug Black and Tiffany Trader

Google Open Sources TensorFlow Version of MorphNet DL Tool

April 18, 2019

Designing optimum deep neural networks remains a non-trivial exercise. “Given the large search space of possible architectures, designing a network from scratch for your specific application can be prohibitively expens Read more…

By John Russell

HPE Extreme Performance Solutions

HPE and Intel® Omni-Path Architecture: How to Power a Cloud

Learn how HPE and Intel® Omni-Path Architecture provide critical infrastructure for leading Nordic HPC provider’s HPCFLOW cloud service.

powercloud_blog.jpgFor decades, HPE has been at the forefront of high-performance computing, and we’ve powered some of the fastest and most robust supercomputers in the world. Read more…

IBM Accelerated Insights

Bridging HPC and Cloud Native Development with Kubernetes

The HPC community has historically developed its own specialized software stack including schedulers, filesystems, developer tools, container technologies tuned for performance and large-scale on-premises deployments. Read more…

Interview with 2019 Person to Watch Michela Taufer

April 18, 2019

Today, as part of our ongoing HPCwire People to Watch focus series, we are highlighting our interview with 2019 Person to Watch Michela Taufer. Michela -- the General Chair of SC19 -- is an ACM Distinguished Scientist. Read more…

By HPCwire Editorial Team

At ASF 2019: The Virtuous Circle of Big Data, AI and HPC

April 18, 2019

We've entered a new phase in IT -- in the world, really -- where the combination of big data, artificial intelligence, and high performance computing is pushing Read more…

By Alex Woodie with Doug Black and Tiffany Trader

Interview with 2019 Person to Watch Michela Taufer

April 18, 2019

Today, as part of our ongoing HPCwire People to Watch focus series, we are highlighting our interview with 2019 Person to Watch Michela Taufer. Michela -- the Read more…

By HPCwire Editorial Team

Intel Gold U-Series SKUs Reveal Single Socket Intentions

April 18, 2019

Intel plans to jump into the single socket market with a portion of its just announced Cascade Lake microprocessor line according to one media report. This isn Read more…

By John Russell

BSC Researchers Shrink Floating Point Formats to Accelerate Deep Neural Network Training

April 15, 2019

Sometimes calculating solutions as precisely as a computer can wastes more CPU resources than is necessary. A case in point is with deep learning. In early stag Read more…

By Ken Strandberg

Intel Extends FPGA Ecosystem with 10nm Agilex

April 11, 2019

The insatiable appetite for higher throughput and lower latency – particularly where edge analytics and AI, network functions, or for a range of datacenter ac Read more…

By Doug Black

Nvidia Doubles Down on Medical AI

April 9, 2019

Nvidia is collaborating with medical groups to push GPU-powered AI tools into clinical settings, including radiology and drug discovery. The GPU leader said Monday it will collaborate with the American College of Radiology (ACR) to provide clinicians with its Clara AI tool kit. The partnership would allow radiologists to leverage AI techniques for diagnostic imaging using their own clinical data. Read more…

By George Leopold

Digging into MLPerf Benchmark Suite to Inform AI Infrastructure Decisions

April 9, 2019

With machine learning and deep learning storming into the datacenter, the new challenge is optimizing infrastructure choices to support diverse ML and DL workfl Read more…

By John Russell

AI and Enterprise Datacenters Boost HPC Server Revenues Past Expectations – Hyperion

April 9, 2019

Building on the big year of 2017 and spurred in part by the convergence of AI and HPC, global revenue for high performance servers jumped 15.6 percent last year Read more…

By Doug Black

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

Why Nvidia Bought Mellanox: ‘Future Datacenters Will Be…Like High Performance Computers’

March 14, 2019

“Future datacenters of all kinds will be built like high performance computers,” said Nvidia CEO Jensen Huang during a phone briefing on Monday after Nvidia revealed scooping up the high performance networking company Mellanox for $6.9 billion. Read more…

By Tiffany Trader

ClusterVision in Bankruptcy, Fate Uncertain

February 13, 2019

ClusterVision, European HPC specialists that have built and installed over 20 Top500-ranked systems in their nearly 17-year history, appear to be in the midst o Read more…

By Tiffany Trader

Intel Reportedly in $6B Bid for Mellanox

January 30, 2019

The latest rumors and reports around an acquisition of Mellanox focus on Intel, which has reportedly offered a $6 billion bid for the high performance interconn Read more…

By Doug Black

It’s Official: Aurora on Track to Be First US Exascale Computer in 2021

March 18, 2019

The U.S. Department of Energy along with Intel and Cray confirmed today that an Intel/Cray supercomputer, "Aurora," capable of sustained performance of one exaf Read more…

By Tiffany Trader

Looking for Light Reading? NSF-backed ‘Comic Books’ Tackle Quantum Computing

January 28, 2019

Still baffled by quantum computing? How about turning to comic books (graphic novels for the well-read among you) for some clarity and a little humor on QC. The Read more…

By John Russell

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

Deep500: ETH Researchers Introduce New Deep Learning Benchmark for HPC

February 5, 2019

ETH researchers have developed a new deep learning benchmarking environment – Deep500 – they say is “the first distributed and reproducible benchmarking s Read more…

By John Russell

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

IBM Bets $2B Seeking 1000X AI Hardware Performance Boost

February 7, 2019

For now, AI systems are mostly machine learning-based and “narrow” – powerful as they are by today's standards, they're limited to performing a few, narro 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

Arm Unveils Neoverse N1 Platform with up to 128-Cores

February 20, 2019

Following on its Neoverse roadmap announcement last October, Arm today revealed its next-gen Neoverse microarchitecture with compute and throughput-optimized si Read more…

By Tiffany Trader

France to Deploy AI-Focused Supercomputer: Jean Zay

January 22, 2019

HPE announced today that it won the contract to build a supercomputer that will drive France’s AI and HPC efforts. The computer will be part of GENCI, the Fre Read more…

By Tiffany Trader

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

Oil and Gas Supercloud Clears Out Remaining Knights Landing Inventory: All 38,000 Wafers

March 13, 2019

The McCloud HPC service being built by Australia’s DownUnder GeoSolutions (DUG) outside Houston is set to become the largest oil and gas cloud in the world th Read more…

By Tiffany Trader

Intel Extends FPGA Ecosystem with 10nm Agilex

April 11, 2019

The insatiable appetite for higher throughput and lower latency – particularly where edge analytics and AI, network functions, or for a range of datacenter ac Read more…

By Doug Black

UC Berkeley Paper Heralds Rise of Serverless Computing in the Cloud – Do You Agree?

February 13, 2019

Almost exactly ten years to the day from publishing of their widely-read, seminal paper on cloud computing, UC Berkeley researchers have issued another ambitious examination of cloud computing - Cloud Programming Simplified: A Berkeley View on Serverless Computing. The new work heralds the rise of ‘serverless computing’ as the next dominant phase of cloud computing. 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