SBIR-STTR Award

Smart Templates for Assisting Portability Layers (STAPL)
Award last edited on: 8/26/2019

Sponsored Program
SBIR
Awarding Agency
DOE
Total Award Amount
$1,774,995
Award Phase
2
Solicitation Topic Code
07b
Principal Investigator
Muthu Baskaran

Company Information

Reservoir Labs Inc

632 Broadway Suite 803
New York, NY 10012
   (212) 780-0527
   peters@reservoir.com
   www.reservoir.com
Location: Multiple
Congr. District: 10
County: New York

Phase I

Contract Number: DE-SC0019522
Start Date: 2/19/2019    Completed: 11/18/2019
Phase I year
2019
Phase I Amount
$225,000
Achieving exascale is critical for improving America’s economic competitiveness and making scientific breakthroughs that will have profound effects on America and the world. The road to exascale is evolving toward advanced computer architectures with diverse processors. Advanced software solutions on programming models and runtimes are needed to obtain the best performance from these new hardware. The advanced programming paradigms are however complex, impose verbose expressions of algorithms, and demand expensive and rare expertise. The goal of this proposal is to develop an exascale software tool as a productive solution towards achieving portable performance across modern and emerging exascale hardware architectures. Our focus will be on developing automatic mapping to a performance portable programming model, namely, Kokkos. Our approach will be to extend an existing high performance computing compiler tool that can automatically parallelize and optimize programs and generate code for the new programming models. In Phase I, we will provide capabilities for automatic transformations and code generation for supporting advanced Kokkos concepts for exascale mapping, namely, heterogeneous mapping, hierarchical parallelism, custom data layout, and scratchpad memory management and data movement. We will also optionally validate and retarget an existing Kokkos code with potential advanced transformations. We will demonstrate the performance and productivity benefits of the tool through important DOE application kernels, namely kernels from E3SM application. STAPL will be a key tool in the exascale ecosystem to attain performance, programmability, and portability. This will enable DOE and the users of exascale ecosystem to push the frontiers of science and technology to enable scientific discovery, enhance national security, and improve competitiveness and global leadership of US economy. During the Phase II time frame, the Government labs will have large installations of new machines (e.g., Aurora21 and CORAL2) and will be striving to maximize the utilization of the Leadership Computing Facilities. A mature product built using the STAPL technology will be useful to the users mapping their applications to such machines. Commercial sectors deal with frequent code modernizations and face the need to port their applications (or write new applications) to modern powerful computing systems. The financial sector, biosciences industry, and the oil and gas industry are relevant examples that will potentially benefit from STAPL. STAPL will be also be a useful tool for the embedded computing market (involving Government and commercial sectors) to adopt embedded applications to the rapidly evolving embedded supercomputers.

Phase II

Contract Number: DE-SC0019522
Start Date: 4/6/2020    Completed: 4/5/2022
Phase II year
2020
Phase II Amount
$1,549,995
Achieving exascale is critical for improving America’s economic competitiveness and making scientific breakthroughs. The road to exascale is evolving toward advanced computer architectures with diverse processors. Advanced software solutions on programming models and runtimes are needed to obtain the best performance from these new hardware. The advanced programming paradigms are however complex, impose verbose expressions of algorithms, and demand expensive and rare expertise. The overall objective of the combined Phase I and Phase II projects is to develop an exascale software tool as a productive solution towards achieving portable performance across modern and emerging exascale hardware architectures. The overall approach is to perform automatic optimization and code generation for emerging and established programming models for exascale that are associated with the Exascale Computing Project (ECP). In Phase I, we accomplished the following: (1) developed and demonstrated compiler capabilities for generating key optimizations for high-performance computing (HPC) and exascale, namely, hierarchical parallelism, heterogeneity, data layout, and data management/movement, through automatic mapping to Kokkos (an ECP software technology); (2) demonstrated productivity and performance benefits through automatic optimization and mapping of Energy Exascale Earth System Model (E3SM) High Order Method Modeling Environment (HOMME) kernels to Kokkos; and (3) published and presented some of the initial results from the project in premier peer-reviewed HPC conferences. STAPL will be a key tool in the exascale ecosystem to attain performance, programmability, and portability. This will enable DOE and the users of exascale ecosystem to push the frontiers of science and technology to enable scientific discovery, enhance national security, and improve competitiveness and global leadership of the US economy. During the Phase II time frame, the Government labs will have large installations of new machines (e.g., Aurora, Frontier, and CORAL2) and will be striving to maximize the utilization of the Leadership Computing Facilities. A mature product built using the STAPL technology will be useful to the users mapping their applications to such machines. Commercial sectors deal with frequent code modernization and face the need to port their applications (or write new applications) to modern powerful computing systems. The financial sector, biosciences industry, and the oil and gas industry are relevant examples that will potentially benefit from STAPL. STAPL will be also be a useful tool for the embedded computing market (involving Government and commercial sectors) to adopt embedded applications to the rapidly evolving embedded supercomputers.