Program Development Tools and Infrastructures: Activities by ASC CSSE/CCE and Partners

Technical Report · Tue Mar 13 00:00:00 EDT 2012

DOI:https://doi.org/10.2172/1037840· OSTI ID:1037840

Schulz, Martin ^[1]; Ahn, Dong ^[1]; de Supinksi, Bronis ^[1]; Gamblin, Todd ^[1]; Gutierrez, Samual ^[2]; Lee, Greg ^[1]; Legrende, Matthew ^[1]; Machado, Anthony ^[2]; Mason, Michael ^[2]; Montoya, David ^[2]; Rajan, Mahesh ^[3]

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1. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
2. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
3. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

Exascale class machines will exhibit a new level of complexity: they will feature an unprecedented number of cores and threads, will most likely be heterogeneous and deeply hierarchical, and offer a range of new hardware techniques (such as speculative threading, transactional memory, programmable prefetching, and programmable accelerators), which all have to be utilized for an application to realize the full potential of the machine. Additionally, users will be faced with less memory per core, fixed total power budgets, and sharply reduced MTBFs. At the same time, it is expected that the complexity of applications will rise sharply for exascale systems, both to implement new science possible at exascale and to exploit the new hardware features necessary to achieve exascale performance. This is particularly true for many of the NNSA codes, which are large and often highly complex integrated simulation codes that push the limits of everything in the system including language features. To overcome these limitations and to enable users to reach exascale performance, users will expect a new generation of tools that address the bottlenecks of exascale machines, that work seamlessly with the (set of) programming models on the target machines, that scale with the machine, that provide automatic analysis capabilities, and that are flexible and modular enough to overcome the complexities and changing demands of the exascale architectures. Further, any tool must be robust enough to handle the complexity of large integrated codes while keeping the user's learning curve low. With the ASC program, in particular the CSSE (Computational Systems and Software Engineering) and CCE (Common Compute Environment) projects, we are working towards a new generation of tools that fulfill these requirements and that provide our users as well as the larger HPC community with the necessary tools, techniques, and methodologies required to make exascale performance a reality.

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: W-7405-ENG-48; AC52-07NA27344
• OSTI ID: 1037840
• Report Number(s): LLNL--TR-537811
• Country of Publication: United States
• Language: English

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