Cristin-prosjekt-ID: 681585
Sist endret: 11. oktober 2019 10:57

Cristin-prosjekt-ID: 681585
Sist endret: 11. oktober 2019 10:57
Prosjekt

Balancing Compute and Memory Performance in Reconfigurable Accelerators with Analytical Modeling (BAMPAM)

prosjektleder

Magnus Jahre
ved Norges teknisk-naturvitenskapelige universitet

prosjekteier / koordinerende forskningsansvarlig enhet

  • Norges teknisk-naturvitenskapelige universitet

Finansiering

  • Norges forskningsråd
    Prosjektkode: 286596

Klassifisering

Vitenskapsdisipliner

Datateknologi

Kategorier

Prosjektkategori

  • Grunnforskning

Kontaktinformasjon

Tidsramme

Aktivt
Start: 15. august 2019 Slutt: 15. september 2023

Beskrivelse Beskrivelse

Tittel

Balancing Compute and Memory Performance in Reconfigurable Accelerators with Analytical Modeling (BAMPAM)

Populærvitenskapelig sammendrag

The exponential growth of computer performance over the last four decades has been a result of continuous improvements in production technology. Dennard scaling -- which describes how transistor dimensions and voltages should be scaled across technology generations to create smaller transistors that consume less power -- has been critical to enable these improvements. By applying Dennard scaling, the number of transistors double with each technology generation while power consumption remains constant. In this sense, Dennard scaling can be seen as an enabler of the performance trend known as Moore's Law.

Unfortunately, it is no longer possible to apply Dennard scaling across technology generations -- as reducing the transistor threshold voltage further exponentially increases static power consumption. At the same time, we have already reached the power dissipation that a practical cooling system can handle. Thus, high-performance computers have become power-limited, and leveraging parallelism, for instance in the form of power-efficient accelerators, is necessary to further improve their performance -- a critical requirement across important domains such as climate modeling, personalized medicine, materials science, chemistry, nanotechnology, automotive, and energy.

In BAMPAM, we will improve the power-efficiency of tightly integrated reconfigurable accelerators by formulating analytical performance models that enable automatically generating accelerator instances with balanced compute and memory performance. A balanced accelerator activates exactly the number of compute units the memory configuration can support -- to ensure high performance -- while disabling remaining units -- to save power.

prosjektdeltakere

prosjektleder

Magnus Jahre

  • Tilknyttet:
    Prosjektleder
    ved Norges teknisk-naturvitenskapelige universitet
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