MANGO Project Tackles Power, Performance and Predictability for Future HPC

By Daniel Hofman, University of Zagreb

June 27, 2016

Under the H2020 High Performance Computing call (Towards exascale high performance computing) MANGO project was awarded funding of 5.8 million euro for three years of research till October 2018. Coordinated by prof. Jose Flich from University of Valencia, consortium includes École polytechnique fédérale de Lausanne, Politecnico di Milano, University of Zagreb, Centro Regionale Information Communication Technology and industrial partners: Eaton Corporation, Pro Design Electronic GmbH, Thales Group and Philips.

The MANGO (exploring Manycore Architectures for Next-GeneratiOn HPC systems) research project aims at addressing power, performance and predictability (the PPP space) in future High-Performance Computing systems. It starts from the fundamental intuition that effective techniques for all three goals ultimately rely on customization to adapt the computing resources to reach the desired Quality of Service (QoS). From this starting point, MANGO will explore different but interrelated mechanisms at various architectural levels, as well as at the level of the system software. In particular, to explore a new positioning across the PPP space, MANGO will investigate system-wide, holistic, proactive thermal and power management aimed at extreme-scale energy efficiency

The performance/power efficiency wall poses the major challenge faced nowadays by HPC. Looking straight at the heart of the problem, the hurdle to the full exploitation of today computing technologies ultimately lies in the gap between the applications’ demand and the underlying computing architecture: the closer the computing system matches the structure of the application, the most efficiently the available computing power is exploited. Consequently, enabling a deeper customization of architectures to applications is the main pathway towards computation power efficiency.

The MANGO project will build on this consideration and will set inherent architecture-level support for application-based customization as one of its underlying pillars. In addition to mere performance and power-efficiency, it is of paramount importance to meet new nonfunctional requirements posed by emerging classes of applications. In particular, a growing number of HPC applications demand some form of time-predictability, or more generally Quality-of-Service (QoS), particularly in those scenarios where correctness depends on both performance and timing requirements and the failure to meet either of them is critical. Examples of such time-critical application include:

  • online video transcoding – the server-side on-the-fly conversion of video contents, which involves very computation-intensive operations on huge amounts of data to be performed within near real-time deadlines.
  • medical imaging – characterized by both stringent low-latency requirements and massive computational demand.

Time predictability and QoS, unfortunately, are a relatively unexplored area in HPC. While traditional HPC systems are based on a “the faster, the better” principle, realtimeness is a feature typically found in systems used for mission-critical applications, where timing constraints usually prevail over performance requirements. In such scenarios, the most straightforward way of ensuring isolation and time-predictability is through resource overprovisioning, which is in striking contrast to power/performance optimization.

MANGO project 1

 

In fact, predictability, power, and performance appear to be three inherently diverging perspectives on HPC. We collectively refer to this range of tradeoffs, well captured in figure above, as the PPP space. The combined optimization of PPP figures is made even more challenging by new delivery models, such as outsourced and cloud based HPC, which are dramatically widening the amount and the type of HPC demand. In fact, cloud enables resource usage and business model flexibility, but it inherently requires virtualization and large scale capacity computing support, where many unrelated, competing applications with very different workloads are served concurrently.

The essential objective of MANGO is to achieve extreme resource efficiency in future QoS-sensitive HPC through ambitious cross-boundary architecture exploration.

The research will investigate the architectural implications of the emerging requirements of HPC applications, aiming at the definition of new-generation high-performance, power-efficient, deeply heterogeneous architectures with native mechanisms for isolation and quality-of-service.

To achieve such ambitious objectives, MANGO will avoid conservative paths. Instead, its disruptive approach will challenge several basic assumptions, exploring new many-core architectures specifically targeted at HPC. The project will involve many different and deeply interrelated mechanisms at various architectural levels:

  • heterogeneous computing cores
  • memory architecture
  • interconnect
  • runtime resource management
  • power monitoring and cooling
  • programming models

In particular, to gain a system-wide understanding of the deep interplay of mechanisms along the PPP axes, MANGO will explore holistic proactive thermal and power management aimed at energy optimization, creating a hitherto inexistent link between hardware and software effects and involving all layers modeling in HPC server, rack, and datacenter conception.

Ultimately, the combined interplay of the multi-level innovative solutions brought by MANGO will result in a new positioning in the PPP space, ensuring sustainable performance as high as 100 PFLOPS for the realistic levels of power consumption delivered to QoS-sensitive applications in large-scale capacity computing scenarios.

Particularly relevant for current European HPC strategies, the results achieved by the project will provide essential building blocks at the architectural level enabling the full realization of the long-term objectives foreseen by the ETP4HPC strategic research agenda.

Project website: www.mango-project.eu

MANGO project 2

 

MANGO project 3

 

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!

And So It Begins…Again – The FY19 Exascale Budget Rollout (and things look good)

February 23, 2018

On February 12, 2018, the Trump administration submitted its Fiscal Year 2019 (FY-19) budget to Congress. The good news for the U.S. exascale program is that the numbers look very good and the support appears to be stron Read more…

By Alex R. Larzelere

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with partner Leibniz Supercomputing Center (LRZ) in Germany. The ser Read more…

By Tiffany Trader

Start-up Aims AI at Automated Tuning of Complex Systems

February 22, 2018

Today’s bigger, more complex, connected and intelligent systems have an exponentially higher number of connections, dependencies, interfaces, protocols and processing architectures that, if not optimized, will hamstrin Read more…

By Doug Black

HPE Extreme Performance Solutions

Experience Memory & Storage Solutions that will Transform Your Data Performance

High performance computing (HPC) has revolutionized the way we harness insight, leading to a dramatic increase in both the size and complexity of HPC systems. Read more…

Do Cryptocurrencies Have a Part to Play in HPC?

February 22, 2018

It’s easy to be distracted by news from the US, China, and now the EU on the state of various exascale projects, but behind the vinyl-wrapped cabinets and well-groomed sales execs are an army of Excel-wielding PMO and Read more…

By Chris Downing

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with par Read more…

By Tiffany Trader

Start-up Aims AI at Automated Tuning of Complex Systems

February 22, 2018

Today’s bigger, more complex, connected and intelligent systems have an exponentially higher number of connections, dependencies, interfaces, protocols and pr Read more…

By Doug Black

HOKUSAI’s BigWaterfall Cluster Extends RIKEN’s Supercomputing Performance

February 21, 2018

RIKEN, Japan’s largest comprehensive research institution, recently expanded the capacity and capabilities of its HOKUSAI supercomputer, a key resource manage Read more…

By Ken Strandberg

Neural Networking Shows Promise in Earthquake Monitoring

February 21, 2018

A team of Harvard University and MIT researchers report their new neural networking method for monitoring earthquakes is more accurate and orders of magnitude faster than traditional approaches. Read more…

By John Russell

HPE Wins $57 Million DoD Supercomputing Contract

February 20, 2018

Hewlett Packard Enterprise (HPE) today revealed details of its massive $57 million HPC contract with the U.S. Department of Defense (DoD). The deal calls for HP Read more…

By Tiffany Trader

Fluid HPC: How Extreme-Scale Computing Should Respond to Meltdown and Spectre

February 15, 2018

The Meltdown and Spectre vulnerabilities are proving difficult to fix, and initial experiments suggest security patches will cause significant performance penal Read more…

By Pete Beckman

Brookhaven Ramps Up Computing for National Security Effort

February 14, 2018

Last week, Dan Coats, the director of Director of National Intelligence for the U.S., warned the Senate Intelligence Committee that Russia was likely to meddle in the 2018 mid-term U.S. elections, much as it stands accused of doing in the 2016 Presidential election. Read more…

By John Russell

AI Cloud Competition Heats Up: Google’s TPUs, Amazon Building AI Chip

February 12, 2018

Competition in the white hot AI (and public cloud) market pits Google against Amazon this week, with Google offering AI hardware on its cloud platform intended Read more…

By Doug Black

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

Japan Unveils Quantum Neural Network

November 22, 2017

The U.S. and China are leading the race toward productive quantum computing, but it's early enough that ultimate leadership is still something of an open questi Read more…

By Tiffany Trader

AMD Showcases Growing Portfolio of EPYC and Radeon-based Systems at SC17

November 13, 2017

AMD’s charge back into HPC and the datacenter is on full display at SC17. Having launched the EPYC processor line in June along with its MI25 GPU the focus he Read more…

By John Russell

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit a Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

Leading Solution Providers

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

Perspective: What Really Happened at SC17?

November 22, 2017

SC is over. Now comes the myriad of follow-ups. Inboxes are filled with templated emails from vendors and other exhibitors hoping to win a place in the post-SC thinking of booth visitors. Attendees of tutorials, workshops and other technical sessions will be inundated with requests for feedback. Read more…

By Andrew Jones

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

GlobalFoundries, Ayar Labs Team Up to Commercialize Optical I/O

December 4, 2017

GlobalFoundries (GF) and Ayar Labs, a startup focused on using light, instead of electricity, to transfer data between chips, today announced they've entered in Read more…

By Tiffany Trader

Tensors Come of Age: Why the AI Revolution Will Help HPC

November 13, 2017

Thirty years ago, parallel computing was coming of age. A bitter battle began between stalwart vector computing supporters and advocates of various approaches to parallel computing. IBM skeptic Alan Karp, reacting to announcements of nCUBE’s 1024-microprocessor system and Thinking Machines’ 65,536-element array, made a public $100 wager that no one could get a parallel speedup of over 200 on real HPC workloads. Read more…

By John Gustafson & Lenore Mullin

Flipping the Flops and Reading the Top500 Tea Leaves

November 13, 2017

The 50th edition of the Top500 list, the biannual publication of the world’s fastest supercomputers based on public Linpack benchmarking results, was released Read more…

By Tiffany Trader

V100 Good but not Great on Select Deep Learning Aps, Says Xcelerit

November 27, 2017

Wringing optimum performance from hardware to accelerate deep learning applications is a challenge that often depends on the specific application in use. A benc Read more…

By John Russell

SC17: Singularity Preps Version 3.0, Nears 1M Containers Served Daily

November 1, 2017

Just a few months ago about half a million jobs were being run daily using Singularity containers, the LBNL-founded container platform intended for HPC. That wa Read more…

By John Russell

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