There are currently four SciDAC Institutes with 24 participating institutions and a total annual funding of $15.5 million. The mission of these SciDAC Institutes is to provide intellectual resources in applied mathematics and computer science, expertise in algorithms and methods, and scientific software tools to advance scientific discovery through modeling and simulation. The development of SciDAC tools and resources by the Institutes is intended for computational systems such as those existing and emerging at the Oak Ridge and Argonne Leadership Computing Facilities, the National Energy Research Scientific Computing Center, and similar world-class computing facilities. Specific goals and objectives for the SciDAC Institutes are:
Although the work of each Institute is not science application-specific, it is application-, architecture-, and Institutes-aware:
Application-aware. One of the primary metrics for the success of the SciDAC Institutes is the extent to which its deliverables are used by application scientists therefore active collaborations among Institutes participants and their domain science partners constitute an integral part of the SciDAC Institutes.
Architecture-aware. The main architectural features of existing and planned computing environments, over the next five years, include heterogeneous nodes (CPUs, GPUs), different memory hierarchies, and varying trade-off costs for computation versus data movement. SciDAC Institutes develop tools and methodologies for coping with and taking full advantage of such architectural complexities.
Institutes-aware. Innovative science projects can be accommodated by the SciDAC Institutes’ pooling of a broad range of computational skills that is otherwise not readily available to DOE domain scientists therefore a key point of SciDAC Institutes is the extent to which Institutes researchers actively collaborate and leverage their expertise in achieving success.
Current SciDAC Institutes
FASTMath – Frameworks, Algorithms, and Scalable Technologies for Mathematics
QUEST – Quantification of Uncertainty in Extreme Scale Computations
SUPER – Institute for Sustained Performance, Energy and Resilience
SDAV—Scalable Data Management, Analysis and Visualization
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