Release to the science community of an open source Data Verified and validated algorithms with demonstrated performance to Fusion software library. Specific quantitative performance support DS era data volumes implemented as software libraries. The Exit Success Criteria metrics should be defined that provide the necessary group discussed the need to evaluate these new algorithms by throughput such that the DS era data volumes could be assessing their impact on science and decision making. processed in a reasonable amount of time. Other Critical None None Milestones & Dates Medium Low Technical Risk (L/M/H) There are well-defined methods to be explored so the main risk is Development of software libraries is relatively low risk, Risk Comments implementing these as efficient algorithms that can support different data however the main risk is schedule risk due to the possibly fusion algorithms that scale to the DS era data volumes. time consuming testing and performance optimization. Cost Risk (L/M/H) Medium Medium The mathematical method development and translation into algorithms While low risk, this is a labor intensive effort due to Cost Comments will be labor intensive and require a sustained effort. Testing and scaling extensive testing and performance tuning required for HPC assessment of the algorithms could increase the overall cost. software libraries. The mathematical methods and algorithm development needs to feed This task requires that the companion task reach a certain Dependency the other technology development task of translating the verified and level of maturity so that verified and validated algorithms are Comments & Notes validate algorithms into reusable software libraries. available to being building the software library.
Exit Success Criteria Verified and validated algorithms with demonstrated performance to support DS era data volumes implemented as software libraries. The group discussed the need to evaluate these new algorithms by assessing their impact on science and decision making. Release to the science community of an open source Data Fusion software library. Specific quantitative performance metrics should be defined that provide the necessary throughput such that the DS era data volumes could be processed in a reasonable amount of time. Other Critical Milestones & Dates None None Technical Risk (L/M/H) Medium Low Risk Comments There are well-defined methods to be explored so the main risk is implementing these as efficient algorithms that can support different data fusion algorithms that scale to the DS era data volumes. Development of software libraries is relatively low risk, however the main risk is schedule risk due to the possibly time consuming testing and performance optimization. Cost Risk (L/M/H) Medium Medium Cost Comments The mathematical method development and translation into algorithms will be labor intensive and require a sustained effort. Testing and scaling assessment of the algorithms could increase the overall cost. While low risk, this is a labor intensive effort due to extensive testing and performance tuning required for HPC software libraries. Dependency Comments & Notes The mathematical methods and algorithm development needs to feed the other technology development task of translating the verified and validate algorithms into reusable software libraries. This task requires that the companion task reach a certain level of maturity so that verified and validated algorithms are available to being building the software library.
2010_AIST%20Workshop_Final_Report.docx