SBIR/STTR Research Award

A Python Interface to Trilinos/Tpetra for High-Level Access to HPC Solvers

Award identifier b1688edc00c431d6ee7ec1a182c817fe9ebbbab819cc514f322b29b0ced3a69cAwarding agency Department of Energy

Award amount

$149,575

Program and phase

SBIR · Phase I

Award year

2012

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Award details

Awarding agency
Department of Energy
Branch
Not reported
Recipient company
ENTHOUGHT, INC.
Proposal award date
2012-02-20
Contract end date
2012-11-19
UEI
NNHLD3C91L41
Solicitation number
DE-FOA-0000577
Topic code
02 b

Research abstract

For many classes of programming problems that require parallel libraries, years of experience are required to effectively use those libraries, and frequently they are difficult to use, requiring complicated programming interfaces. The large time investment and limited usability prohibit typical domain specialists, who have limited programming expertise, from creating parallel codes and benefiting from parallel resources. Programs that can make this time investment typically have huge resources at their disposal, such as the Advanced Simulation & amp; Computing (ASC) campaign, or the Scientific Discovery through Advanced Computing (SciDAC) program. The motivation for industry users to use parallel libraries will only grow with time, as multi-core systems are becoming more widely available on commodity desktop and laptop systems, and it is not far off before hundred-core desktops and laptops are common. We propose to design a high-level interface to the Trilinos Tpetra parallel linear algebra library in the expressive and user-friendly Python language. This interface will make parallel linear algebra (1) easier to use via a simplified user interface, (2) more intuitive through features such as advanced indexing, and (3) more useful by enabling access to it from the already extensive Python scientific software stack. Commercial applications and other benefits: The project will result in better utilization of existing HPC resources and will facilitate a decrease in the total time to market from concept to implementation, improving the competitiveness of US industries, universities and defense organizations. The benefit to the public will be observed in diverse applications that use parallel linear algebra libraries for simulation and modeling: product design and manufacturing, pharmaceuticals, thermal management, network and data transmission design, medical imaging, operational logistics, environmental project planning, and risk and performance assessment, to name some examples.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

5 SBIR/STTR records share this UEI (2004–2017). Reported award amounts total $3,478,710. Reported amounts are not federal obligations.

Phases: Phase II, Phase I, Phase II – Direct to Phase II

Agencies: Department of Defense, Department of Energy

Agency intelligence

Department of Energy

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