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FINANCIAL ASSISTANCE FUNDING OPPORTUNITY ANNOUNCEMENT Small Business Innovation Research (SBIR) Small Business Technology Transfer (STTR
NOTE: The Solicitations and topics listed on this site are copies from the various SBIR agency solicitations and are not necessarily the latest and most up-to-date. For this reason, you should use the agency link listed below which will take you directly to the appropriate agency server where you can read the official version of this solicitation and download the appropriate forms and rules.
The official link for this solicitation is: http:--science.doe.gov-grants-pdf-SC_FOA_0000969.pdf
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Over the past 30 years, The Department of Energys (DOE) supercomputing program has played an increasingly important role in the scientific discovery process by allowing scientists to create more accurate models of complex systems, simulate problems once thought to be impossible, and analyze the increasing amount of data generated by experiments. Computational Science has become the third pillar of science, along with theory and experimentation. However despite the great potential of modeling and simulation to increase understanding of a variety of important engineering and manufacturing challenges, High Performance Computing (HPC) has been underutilized due to application complexity, the need for substantial in-house expertise, and perceived high capital costs. This topic is specifically focused on bringing HPC solutions and capabilities to the advanced manufacturing and engineering market sectors.
Many tools and services have been developed over the years to support the HPC user and development community. These tools (debuggers, profilers, workflow engines, low-level libraries, etc.), although very powerful, take a good deal of time and effort to learn and use. For a company to utilize HPC in the development of their product or service they need to invest a substantial amount in learning these tools and services. This presents an insurmountable barrier for many organizations. If the tools were easier to use and more intuitive, they could be more widely utilized. Grant applications are sought that will help make HPC tools and services easier to use for the experienced (not expert) user, through enhanced or simplified user interfaces, consolidation of tools into a common environment, common frameworks, etc. Grant applications must establish how the proposed tools and services can greatly increase the ease of use for a less-experienced HPC user or developer.
The Office of Science (SC) Office of Advanced Scientific Computing (ASCR) has invested millions of dollars in the development of HPC software in the areas of modeling and simulation, solvers, and tools. Many of these tools are open source, but are complex expert level tools. The expertise required to install, utilize and run these assets poses a significant barrier to many organizations due to the levels of complexity built into them to facilitate scientific discovery and research, but such complexity may not necessarily be required for industrial applications. Grant applications are specifically sought that will take a component or components of codes developed via the Scientific Discovery through Advanced Computing (SciDAC) program, or other ASCR programs, and shrink wrap them into tools that require a lower level of expertise to utilize. This may include Graphical User Interface Designs (GUIs), simplification of user input, decreasing complexity of a code by stripping out components, user support tools-services, or other ways that make the code more widely useable. Applicants may also choose to harden the codes developed by other projects provided that the potential industrial uses support the DOE mission. In addition applicants may choose to strip out code components, harden them and join them with already mature code tools and-or suites of tools to increase the overall toolset and scalability of commercial software.
In addition to the specific subtopics listed above, the Department invites grant applications in other areas that fall within the scope of the topic description above.