1. Priority Research Direction: Portable de facto standard software frameworks Key challenges Establish forums for multi-institutional discussions. Define standard interfaces and tool chains. Develop domain-specific languages (augmenting existing languages), data representations. Develop organizations for tools support. Develop framework capabilities to accommodate exascale PMs, algorithms, libraries and resilience. Educate application base on the availability and use of the frameworks. Numerous diverse frameworks exist. Some apps resistant to heavy framework dependency. Good coordination at institution level, little above that. Different tool chains used. Keeping institutional identity while fostering multi- institutional collaboration. Exascale software complexity common to all applications. Focused funding on reusable software frameworks. Promotion of best practices across many projects. Leverage investments in common tool-chains. Summary of research direction Potential impact on software component Potential impact on usability, capability, and breadth of community Optimal reuse of high quality software tools and methodologies in applications. Shortened development time for applications. Rapid deployment of new peta/exascale algorithms and software capabilities. Enable multi-disciplinary, multi-agency, multi-national collaborations. Some impact within 2years, optimal within 10.

2. 4.2.2 Frameworks Frameworks: Software environments that provide reusable code and a documented, extensible structure for building in new capabilities on a domain-specific scale. First frameworks workshop Catalog of existing frameworks Identify gaps and overlaps, form standards committees Standard interoperability mechanisms defined Planned incorporation of exascale-essential capabilities (PMs, algorithms, libs) Deployment of exascale-capable frameworks 2010201120122013201420152016201720182019 Framework Readiness

3. 4.2.2 Frameworks Technology drivers: – Exascale systems will demand broad application changes. – Many new applications under development that require infrastructure (that frameworks can provide). – Many potential applications are possible only if a framework is available. – Exascale computing requires multi-disciplinary collaboration. Alternative R&D strategies: – No frameworks, custom software stacks. – Brand new programming model, clean slate framework development. Recommended research agenda: – Identify important international and domain-specific framework efforts. – Convene international workshops to catalog framework capabilities, best practices, tool- chains and gaps. – Work with programming models, libraries,algorithms and runtime efforts to incorporate new capabilities needed for exascale. – Convene committees to define interoperability standards and tool chain conventions. Publish standard specs. – Deploy standard components and full frameworks for peta/exascale systems. Crosscutting considerations – Programming models, libraries, algorithms and runtime efforts are critical collaborators. – Application teams are ultimate framework customers and collaborators. – Frameworks (and libraries) would be part of standard software stack.

4. Frameworks R&D (1) Multi-institutional/multi-project collaboration: – Existing applications, frameworks need viable multi-institution/project collaboration model. – Develop a collaboration model that is “win-win” for existing efforts and meta-efforts. Tool chain development/selection: – Evaluate common tool needs and availability. – Develop/select common set of configure/compile/debug/etc tools. Programming model evaluation/adoption: – MPI-only not sufficient. Evaluate and select programming models. – Develop migration strategy to migrate from MPI-only to new PMs. Data placement: – App/library interfaces more complicated. – Data placement semantics required. Load balancing critical. – Develop collaboration model for app/library data placement and balancing.

5. Frameworks R&D (2) Resiliency: – Hard and soft errors may increase dramatically. – App-driven fault detection/recovery /resilience framework needed. – Develop resilience framework with customization capabilities. Multi-component simulations: – Multi-scale, multi-physics simulation need inter-component support. – Develop workflow modeling support (“workbench”). – Develop data models and data sharing capabilities. Software libraries: – Libraries provide critical enabling algorithms implementations. – Develop uniform interfaces to variety of libraries via a libraries framework.

6. Frameworks Deliverables (1) Workshops: 2010, 2011, regularly after. – Bring together members from key existing framework efforts, algorithm/library developers, programming models. – Workshop 1: Capabilities/Gaps analysis. First opportunities for multi-institutional frameworks. Best practices from existing efforts. Common tool chain requirements. Possible win-win scenarios. – Workshop 2: Plan for programming model evaluations. Develop library data model semantics. – Workshop 3: App-driven resilience models.

7. Frameworks Deliverables (2) Develop first 2 app and first library frameworks, 2015. – Mine components from existing capabilities. – Implement common tool chain, programming model, first resilience harness, library interfaces. – Breadth first approach. Develop 2-3 additional app frameworks, 2017. – Leverage infrastructure/design knowledge from first efforts. – Develop inter-component coupling capabilities (e.g., data sharing). Demonstrate full-scale application capabilities on Exascale system, 2018.