Cristin-prosjekt-ID: 483944
Sist endret: 15. september 2015, 18:22

Cristin-prosjekt-ID: 483944
Sist endret: 15. september 2015, 18:22
Prosjekt

PRoductivity and Energy-efficiency through Abstraction-based Parallel Programming (PREAPP)

prosjektleder

Hoai Phuong Ha
ved Institutt for informatikk ved UiT Norges arktiske universitet

prosjekteier / koordinerende forskningsansvarlig enhet

  • UiT Norges arktiske universitet

Finansiering

  • TotalbudsjettNOK 7.895.000
  • Norges forskningsråd
    Prosjektkode: 231746

Klassifisering

Vitenskapsdisipliner

Informasjons- og kommunikasjonsteknologi

Kategorier

Prosjektkategori

  • Grunnforskning

Kontaktinformasjon

Telefon
776 44032
Sted
Ha, Hoai Phuong

Tidsramme

Avsluttet
Start: 15. september 2015 Slutt: 31. mars 2018

Beskrivelse Beskrivelse

Tittel

PRoductivity and Energy-efficiency through Abstraction-based Parallel Programming (PREAPP)

Populærvitenskapelig sammendrag

In today's exponential world of digital data, big data services have made the power consumption the lion's share of the total cost. For instance, Google data centers consume almost 260 MW, about a quarter of the output of a nuclear power plant, enough to  power 200 000 homes. Energy efficiency is therefore considered a major criterion for "sustainable" computing systems and services over the data deluge. However, energy-efficient computing systems make parallel programming even more complex and thereby les s robust due to requirements of massive parallelism, heterogeneity and data locality.

The PREAPP project aims to devise novel programming models that will form foundations for a paradigm shift from energy "blind" to energy "aware" software development. T he new models will enable one order of magnitude improvement in energy efficiency in comparison with today's multicore computing, thereby greatly advancing green computing and sustainable services. The new models will facilitate unprecedented productivity  for implementing scientific big data applications that run effectively on large-scale high-performance computing (HPC) platforms, which are based on cutting-edge manycore architectures. The threshold of adopting large-scale parallel computing will thus b e considerably lowered for a large number of computational scientists in several disciplines.

prosjektdeltakere

prosjektleder

Hoai Phuong Ha

  • Tilknyttet:
    Prosjektleder
    ved Institutt for informatikk ved UiT Norges arktiske universitet
1 - 1 av 1

Resultater Resultater

The Arctic Green Computing Group.

Umar, Ibrahim; Tran, Ngoc Nha Vi; Shariati, Saeed; Anshus, Otto; Ha, Hoai Phuong. 2015, EU Network of Excellence HiPEAC Computing System Week. UITPoster

Energy-efficient and Locality-aware Concurrent Search Tree.

Umar, Ibrahim; Anshus, Otto; Ha, Hoai Phuong. 2015, fEEDBACk Workshop Energy Efficient Distributed and Parallel Computing. UITVitenskapelig foredrag

DeltaTree: A Locality-aware Concurrent Search Tree.

Umar, Ibrahim; Anshus, Otto; Ha, Hoai Phuong. 2015, ACM SIGMETRICS 2015 International Conference on Measurement and Modeling of Computer Systems. UITPoster

DeltaTree: A locality-aware concurrent search tree.

Umar, Ibrahim; Anshus, Otto; Ha, Hoai Phuong. 2015, Performance Evaluation Review. UITVitenskapelig artikkel
1 - 4 av 4