The NASA SBIR and STTR programs fund the research, development, and demonstration of innovative technologies that fulfill NASA needs as described in the annual Solicitations and have significant potential for successful commercialization. If you are a small business concern (SBC) with 500 or fewer employees or a non-profit RI such as a university or a research laboratory with ties to an SBC, then NASA encourages you to learn more about the SBIR and STTR programs as a potential source of seed funding for the development of your innovations.
The SBIR and STTR programs have 3 phases:
The SBIR and STTR Phase I contracts last for 6 months with a maximum funding of $125,000, and Phase II contracts last for 24 months with a maximum funding of $750,000 - $1.5 million.
Opportunity for Continued Technology Development Post-Phase II:
The NASA SBIR/STTR Program currently has in place two initiatives for supporting its small business partners past the basic Phase I and Phase II elements of the program that emphasize opportunities for commercialization. Specifically, the NASA SBIR/STTR Program has the Phase II Enhancement (Phase II-E) and Phase II eXpanded (Phase II-X) contract options.
Please review the links below to obtain more information on the SBIR/STTR programs.
Provides an overview of the SBIR and STTR programs as implemented by NASA
Provides access to the annual SBIR/STTR Solicitations containing detailed information on the program eligibility requirements, proposal instructions and research topics and subtopics
Schedule and links for the SBIR/STTR solicitations and selection announcements
Federal and non-Federal sources of assistance for small business
Search our complete archive of awarded project abstracts to learn about what NASA has funded
Still have questions? Visit the program FAQs
","parentProgram":{"ableToSelect":false,"isActive":true,"description":"Catalyst is a portfolio of early stage programs that specialize in different innovation constituencies and mechanisms to push the state of the art in aerospace technology development","programId":92327,"responsibleMd":{"canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":""},"title":"Catalyst","manageGaps":false,"acronymOrTitle":"Catalyst"},"parentProgramId":92327,"programId":73,"responsibleMd":{"organizationId":4875,"organizationName":"Space Technology Mission Directorate","acronym":"STMD","organizationType":"NASA_Mission_Directorate","canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":"NASA Mission Directorate"},"responsibleMdOffice":4875,"stockImageFileId":36648,"title":"Small Business Innovation Research/Small Business Tech Transfer","manageGaps":false,"acronymOrTitle":"SBIR/STTR"},"description":"Many large-scale numerical simulations can be broken down into common mathematical routines. While the applications may differ, the need to perform functions such as matrix solves, Fourier transforms, or eigenvalue analysis routinely arise. Consequently, targeting fast, efficient implementations of these methods will benefit a large number of applications. Graphics Processing Units (GPUs) are emerging as an attractive platform to perform these types of simulations. There FLOPS/Watt and FLOPS/dollar figures are far below competing alternatives. In previous work, EM Photonics has implemented dense matrix solvers using a hybrid GPU/multicore microprocessor approach. This has shown the ability to significantly outperform either platform when used independently. In this project, we will develop a complimentary library focused on performing routines on sparse matrices. This will be extremely valuable to a wide set of users including those doing finite-element analysis and computational fluid dynamics. Using GPUs, users are able to build single workstations with an excess of four teraFLOPS of computational power as well as create large, high-performance computing systems that are efficient in terms of both cost and power. By leveraging libraries such as the ones we will develop for this project, the user is shielded from the intricacies of GPU programming while still able to access their computational performance.","benefits":"The need to solve sparse matrices arises from numerous scientific computing and numerical analysis applications. One major category that requires sparse matrix solutions includes solvers that use finite element analysis. This technique can be used for fields such as electromagnetics, heat transfer, structural analysis, chemical interactions, and environmental phenomena, among many others. Additionally, sparse matrices can arise in image processing, classification, combustion analysis, and fluid modeling techniques. It is extremely common for numerical algorithms to result in the need to solve sparse matrices. By significantly accelerating such solvers, you have the opportunity to affect an extremely wide range of fields.The NASA SBIR and STTR programs fund the research, development, and demonstration of innovative technologies that fulfill NASA needs as described in the annual Solicitations and have significant potential for successful commercialization. If you are a small business concern (SBC) with 500 or fewer employees or a non-profit RI such as a university or a research laboratory with ties to an SBC, then NASA encourages you to learn more about the SBIR and STTR programs as a potential source of seed funding for the development of your innovations.
The SBIR and STTR programs have 3 phases:
The SBIR and STTR Phase I contracts last for 6 months with a maximum funding of $125,000, and Phase II contracts last for 24 months with a maximum funding of $750,000 - $1.5 million.
Opportunity for Continued Technology Development Post-Phase II:
The NASA SBIR/STTR Program currently has in place two initiatives for supporting its small business partners past the basic Phase I and Phase II elements of the program that emphasize opportunities for commercialization. Specifically, the NASA SBIR/STTR Program has the Phase II Enhancement (Phase II-E) and Phase II eXpanded (Phase II-X) contract options.
Please review the links below to obtain more information on the SBIR/STTR programs.
Provides an overview of the SBIR and STTR programs as implemented by NASA
Provides access to the annual SBIR/STTR Solicitations containing detailed information on the program eligibility requirements, proposal instructions and research topics and subtopics
Schedule and links for the SBIR/STTR solicitations and selection announcements
Federal and non-Federal sources of assistance for small business
Search our complete archive of awarded project abstracts to learn about what NASA has funded
Still have questions? Visit the program FAQs
","parentProgram":{"ableToSelect":false,"isActive":true,"description":"Catalyst is a portfolio of early stage programs that specialize in different innovation constituencies and mechanisms to push the state of the art in aerospace technology development","programId":92327,"responsibleMd":{"canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":""},"title":"Catalyst","manageGaps":false,"acronymOrTitle":"Catalyst"},"parentProgramId":92327,"programId":73,"responsibleMd":{"organizationId":4875,"organizationName":"Space Technology Mission Directorate","acronym":"STMD","organizationType":"NASA_Mission_Directorate","canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":"NASA Mission Directorate"},"responsibleMdOffice":4875,"stockImageFileId":36648,"title":"Small Business Innovation Research/Small Business Tech Transfer","manageGaps":false,"acronymOrTitle":"SBIR/STTR"},"description":"Many large-scale numerical simulations can be broken down into common mathematical routines. While the applications may differ, the need to perform functions such as matrix solves, Fourier transforms, or eigenvalue analysis routinely arise. Consequently, targeting fast, efficient implementations of these methods will benefit a large number of applications. Graphics Processing Units (GPUs) are emerging as an attractive platform to perform these types of simulations. There FLOPS/Watt and FLOPS/dollar figures are far below competing alternatives. In previous work, EM Photonics has implemented dense matrix solvers using a hybrid GPU/multicore microprocessor approach. This has shown the ability to significantly outperform either platform when used independently. In this project, we will develop a complimentary library focused on performing routines on sparse matrices. This will be extremely valuable to a wide set of users including those doing finite-element analysis and computational fluid dynamics. Using GPUs, users are able to build single workstations with an excess of four teraFLOPS of computational power as well as create large, high-performance computing systems that are efficient in terms of both cost and power. By leveraging libraries such as the ones we will develop for this project, the user is shielded from the intricacies of GPU programming while still able to access their computational performance.","benefits":"The need to solve sparse matrices arises from numerous scientific computing and numerical analysis applications. One major category that requires sparse matrix solutions includes solvers that use finite element analysis. This technique can be used for fields such as electromagnetics, heat transfer, structural analysis, chemical interactions, and environmental phenomena, among many others. Additionally, sparse matrices can arise in image processing, classification, combustion analysis, and fluid modeling techniques. It is extremely common for numerical algorithms to result in the need to solve sparse matrices. By significantly accelerating such solvers, you have the opportunity to affect an extremely wide range of fields.The NASA SBIR and STTR programs fund the research, development, and demonstration of innovative technologies that fulfill NASA needs as described in the annual Solicitations and have significant potential for successful commercialization. If you are a small business concern (SBC) with 500 or fewer employees or a non-profit RI such as a university or a research laboratory with ties to an SBC, then NASA encourages you to learn more about the SBIR and STTR programs as a potential source of seed funding for the development of your innovations.
The SBIR and STTR programs have 3 phases:
The SBIR and STTR Phase I contracts last for 6 months with a maximum funding of $125,000, and Phase II contracts last for 24 months with a maximum funding of $750,000 - $1.5 million.
Opportunity for Continued Technology Development Post-Phase II:
The NASA SBIR/STTR Program currently has in place two initiatives for supporting its small business partners past the basic Phase I and Phase II elements of the program that emphasize opportunities for commercialization. Specifically, the NASA SBIR/STTR Program has the Phase II Enhancement (Phase II-E) and Phase II eXpanded (Phase II-X) contract options.
Please review the links below to obtain more information on the SBIR/STTR programs.
Provides an overview of the SBIR and STTR programs as implemented by NASA
Provides access to the annual SBIR/STTR Solicitations containing detailed information on the program eligibility requirements, proposal instructions and research topics and subtopics
Schedule and links for the SBIR/STTR solicitations and selection announcements
Federal and non-Federal sources of assistance for small business
Search our complete archive of awarded project abstracts to learn about what NASA has funded
Still have questions? Visit the program FAQs
","parentProgram":{"ableToSelect":false,"isActive":true,"description":"Catalyst is a portfolio of early stage programs that specialize in different innovation constituencies and mechanisms to push the state of the art in aerospace technology development","programId":92327,"responsibleMd":{"canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":""},"title":"Catalyst","manageGaps":false,"acronymOrTitle":"Catalyst"},"parentProgramId":92327,"programId":73,"responsibleMd":{"organizationId":4875,"organizationName":"Space Technology Mission Directorate","acronym":"STMD","organizationType":"NASA_Mission_Directorate","canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":"NASA Mission Directorate"},"responsibleMdOffice":4875,"stockImageFileId":36648,"title":"Small Business Innovation Research/Small Business Tech Transfer","manageGaps":false,"acronymOrTitle":"SBIR/STTR"},"description":"Many large-scale numerical simulations can be broken down into common mathematical routines. While the applications may differ, the need to perform functions such as matrix solves, Fourier transforms, or eigenvalue analysis routinely arise. Consequently, targeting fast, efficient implementations of these methods will benefit a large number of applications. Graphics Processing Units (GPUs) are emerging as an attractive platform to perform these types of simulations. There FLOPS/Watt and FLOPS/dollar figures are far below competing alternatives. In previous work, EM Photonics has implemented dense matrix solvers using a hybrid GPU/multicore microprocessor approach. This has shown the ability to significantly outperform either platform when used independently. In this project, we will develop a complimentary library focused on performing routines on sparse matrices. This will be extremely valuable to a wide set of users including those doing finite-element analysis and computational fluid dynamics. Using GPUs, users are able to build single workstations with an excess of four teraFLOPS of computational power as well as create large, high-performance computing systems that are efficient in terms of both cost and power. By leveraging libraries such as the ones we will develop for this project, the user is shielded from the intricacies of GPU programming while still able to access their computational performance.","benefits":"The need to solve sparse matrices arises from numerous scientific computing and numerical analysis applications. One major category that requires sparse matrix solutions includes solvers that use finite element analysis. This technique can be used for fields such as electromagnetics, heat transfer, structural analysis, chemical interactions, and environmental phenomena, among many others. Additionally, sparse matrices can arise in image processing, classification, combustion analysis, and fluid modeling techniques. It is extremely common for numerical algorithms to result in the need to solve sparse matrices. By significantly accelerating such solvers, you have the opportunity to affect an extremely wide range of fields.The NASA SBIR and STTR programs fund the research, development, and demonstration of innovative technologies that fulfill NASA needs as described in the annual Solicitations and have significant potential for successful commercialization. If you are a small business concern (SBC) with 500 or fewer employees or a non-profit RI such as a university or a research laboratory with ties to an SBC, then NASA encourages you to learn more about the SBIR and STTR programs as a potential source of seed funding for the development of your innovations.
The SBIR and STTR programs have 3 phases:
The SBIR and STTR Phase I contracts last for 6 months with a maximum funding of $125,000, and Phase II contracts last for 24 months with a maximum funding of $750,000 - $1.5 million.
Opportunity for Continued Technology Development Post-Phase II:
The NASA SBIR/STTR Program currently has in place two initiatives for supporting its small business partners past the basic Phase I and Phase II elements of the program that emphasize opportunities for commercialization. Specifically, the NASA SBIR/STTR Program has the Phase II Enhancement (Phase II-E) and Phase II eXpanded (Phase II-X) contract options.
Please review the links below to obtain more information on the SBIR/STTR programs.
Provides an overview of the SBIR and STTR programs as implemented by NASA
Provides access to the annual SBIR/STTR Solicitations containing detailed information on the program eligibility requirements, proposal instructions and research topics and subtopics
Schedule and links for the SBIR/STTR solicitations and selection announcements
Federal and non-Federal sources of assistance for small business
Search our complete archive of awarded project abstracts to learn about what NASA has funded
Still have questions? Visit the program FAQs
","parentProgram":{"ableToSelect":false,"isActive":true,"description":"Catalyst is a portfolio of early stage programs that specialize in different innovation constituencies and mechanisms to push the state of the art in aerospace technology development","programId":92327,"responsibleMd":{"canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":""},"title":"Catalyst","manageGaps":false,"acronymOrTitle":"Catalyst"},"parentProgramId":92327,"programId":73,"responsibleMd":{"organizationId":4875,"organizationName":"Space Technology Mission Directorate","acronym":"STMD","organizationType":"NASA_Mission_Directorate","canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":"NASA Mission Directorate"},"responsibleMdOffice":4875,"stockImageFileId":36648,"title":"Small Business Innovation Research/Small Business Tech Transfer","manageGaps":false,"acronymOrTitle":"SBIR/STTR"},"description":"At the heart of scientific computing and numerical analysis are linear algebra solvers. In scientific computing, the focus is on the partial differential equations (PDEs) that arise from computational fluid dynamics (CFD), climate modeling, astrophysics, and structural and heat analysis that cannot be solved analytically. Certain problem formulations lead to sparse matrices, in which the majority of matrix elements are zero. Special attention is required when computing on sparse matrices in order to avoid using unrealistic amounts of memory or produce ill-performing software. Such topics have been the subject of considerable research and the limits of CPU-based performance have been reached. Recently, the graphics processing unit (GPU) has emerged as an attractive platform for high performance computing. The modern GPU boasts over 1 TFLOPS performance and as much as 6 GB onboard memory, but harnessing the power can be challenging. A library-based approach is common for HPC, with most applications using several libraries to offload well-known tasks. EM Photonics maintains a library of GPU-accelerated dense linear algebra solvers that has over 5000 users. In this project we will extend this library to include a wide range of sparse solvers, including many that have direct relevance to NASA projects.","benefits":"Sparse solvers have applications in the entire FVM and FEM space that further expands the applicability of our project to a large number of fields involved with modeling and simulation. For instance, the models used by circuit simulation, heat transfer, and structural mechanics can all be represented by very large sparse matrices. Accelerated sparse solvers will allow engineers to more quickly turn around designs with increased detail and accuracy. Large sparse matrices commonly arise in other fields involving statistics and optimization where a large amount number of elements have various interactions. For example, electrical power systems, traffic flow optimization, economics, search index rankings, and the modeling of chemical processes are just a small sample of fields where the interaction of a large number coupled elements are represented through sparse matrices. Accelerated sparse solvers and decompositions will allow scientists to rapidly study larger problems in less time.The NASA SBIR and STTR programs fund the research, development, and demonstration of innovative technologies that fulfill NASA needs as described in the annual Solicitations and have significant potential for successful commercialization. If you are a small business concern (SBC) with 500 or fewer employees or a non-profit RI such as a university or a research laboratory with ties to an SBC, then NASA encourages you to learn more about the SBIR and STTR programs as a potential source of seed funding for the development of your innovations.
The SBIR and STTR programs have 3 phases:
The SBIR and STTR Phase I contracts last for 6 months with a maximum funding of $125,000, and Phase II contracts last for 24 months with a maximum funding of $750,000 - $1.5 million.
Opportunity for Continued Technology Development Post-Phase II:
The NASA SBIR/STTR Program currently has in place two initiatives for supporting its small business partners past the basic Phase I and Phase II elements of the program that emphasize opportunities for commercialization. Specifically, the NASA SBIR/STTR Program has the Phase II Enhancement (Phase II-E) and Phase II eXpanded (Phase II-X) contract options.
Please review the links below to obtain more information on the SBIR/STTR programs.
Provides an overview of the SBIR and STTR programs as implemented by NASA
Provides access to the annual SBIR/STTR Solicitations containing detailed information on the program eligibility requirements, proposal instructions and research topics and subtopics
Schedule and links for the SBIR/STTR solicitations and selection announcements
Federal and non-Federal sources of assistance for small business
Search our complete archive of awarded project abstracts to learn about what NASA has funded
Still have questions? Visit the program FAQs
","parentProgram":{"ableToSelect":false,"isActive":true,"description":"Catalyst is a portfolio of early stage programs that specialize in different innovation constituencies and mechanisms to push the state of the art in aerospace technology development","programId":92327,"responsibleMd":{"canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":""},"title":"Catalyst","manageGaps":false,"acronymOrTitle":"Catalyst"},"parentProgramId":92327,"programId":73,"responsibleMd":{"organizationId":4875,"organizationName":"Space Technology Mission Directorate","acronym":"STMD","organizationType":"NASA_Mission_Directorate","canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":"NASA Mission Directorate"},"responsibleMdOffice":4875,"stockImageFileId":36648,"title":"Small Business Innovation Research/Small Business Tech Transfer","manageGaps":false,"acronymOrTitle":"SBIR/STTR"},"description":"Many large-scale numerical simulations can be broken down into common mathematical routines. While the applications may differ, the need to perform functions such as matrix solves, Fourier transforms, or eigenvalue analysis routinely arise. Consequently, targeting fast, efficient implementations of these methods will benefit a large number of applications. Graphics Processing Units (GPUs) are emerging as an attractive platform to perform these types of simulations. There FLOPS/Watt and FLOPS/dollar figures are far below competing alternatives. In previous work, EM Photonics has implemented dense matrix solvers using a hybrid GPU/multicore microprocessor approach. This has shown the ability to significantly outperform either platform when used independently. In this project, we will develop a complimentary library focused on performing routines on sparse matrices. This will be extremely valuable to a wide set of users including those doing finite-element analysis and computational fluid dynamics. Using GPUs, users are able to build single workstations with an excess of four teraFLOPS of computational power as well as create large, high-performance computing systems that are efficient in terms of both cost and power. By leveraging libraries such as the ones we will develop for this project, the user is shielded from the intricacies of GPU programming while still able to access their computational performance.","benefits":"The need to solve sparse matrices arises from numerous scientific computing and numerical analysis applications. One major category that requires sparse matrix solutions includes solvers that use finite element analysis. This technique can be used for fields such as electromagnetics, heat transfer, structural analysis, chemical interactions, and environmental phenomena, among many others. Additionally, sparse matrices can arise in image processing, classification, combustion analysis, and fluid modeling techniques. It is extremely common for numerical algorithms to result in the need to solve sparse matrices. By significantly accelerating such solvers, you have the opportunity to affect an extremely wide range of fields.The NASA SBIR and STTR programs fund the research, development, and demonstration of innovative technologies that fulfill NASA needs as described in the annual Solicitations and have significant potential for successful commercialization. If you are a small business concern (SBC) with 500 or fewer employees or a non-profit RI such as a university or a research laboratory with ties to an SBC, then NASA encourages you to learn more about the SBIR and STTR programs as a potential source of seed funding for the development of your innovations.
The SBIR and STTR programs have 3 phases:
The SBIR and STTR Phase I contracts last for 6 months with a maximum funding of $125,000, and Phase II contracts last for 24 months with a maximum funding of $750,000 - $1.5 million.
Opportunity for Continued Technology Development Post-Phase II:
The NASA SBIR/STTR Program currently has in place two initiatives for supporting its small business partners past the basic Phase I and Phase II elements of the program that emphasize opportunities for commercialization. Specifically, the NASA SBIR/STTR Program has the Phase II Enhancement (Phase II-E) and Phase II eXpanded (Phase II-X) contract options.
Please review the links below to obtain more information on the SBIR/STTR programs.
Provides an overview of the SBIR and STTR programs as implemented by NASA
Provides access to the annual SBIR/STTR Solicitations containing detailed information on the program eligibility requirements, proposal instructions and research topics and subtopics
Schedule and links for the SBIR/STTR solicitations and selection announcements
Federal and non-Federal sources of assistance for small business
Search our complete archive of awarded project abstracts to learn about what NASA has funded
Still have questions? Visit the program FAQs
","parentProgram":{"ableToSelect":false,"isActive":true,"description":"Catalyst is a portfolio of early stage programs that specialize in different innovation constituencies and mechanisms to push the state of the art in aerospace technology development","programId":92327,"responsibleMd":{"canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":""},"title":"Catalyst","manageGaps":false,"acronymOrTitle":"Catalyst"},"parentProgramId":92327,"programId":73,"responsibleMd":{"organizationId":4875,"organizationName":"Space Technology Mission Directorate","acronym":"STMD","organizationType":"NASA_Mission_Directorate","canUserEdit":false,"locationEdit":false,"organizationRolePretty":"","organizationTypePretty":"NASA Mission Directorate"},"responsibleMdOffice":4875,"stockImageFileId":36648,"title":"Small Business Innovation Research/Small Business Tech Transfer","manageGaps":false,"acronymOrTitle":"SBIR/STTR"},"description":"At the heart of scientific computing and numerical analysis are linear algebra solvers. In scientific computing, the focus is on the partial differential equations (PDEs) that arise from computational fluid dynamics (CFD), climate modeling, astrophysics, and structural and heat analysis that cannot be solved analytically. Certain problem formulations lead to sparse matrices, in which the majority of matrix elements are zero. Special attention is required when computing on sparse matrices in order to avoid using unrealistic amounts of memory or produce ill-performing software. Such topics have been the subject of considerable research and the limits of CPU-based performance have been reached. Recently, the graphics processing unit (GPU) has emerged as an attractive platform for high performance computing. The modern GPU boasts over 1 TFLOPS performance and as much as 6 GB onboard memory, but harnessing the power can be challenging. A library-based approach is common for HPC, with most applications using several libraries to offload well-known tasks. EM Photonics maintains a library of GPU-accelerated dense linear algebra solvers that has over 5000 users. In this project we will extend this library to include a wide range of sparse solvers, including many that have direct relevance to NASA projects.","benefits":"Sparse solvers have applications in the entire FVM and FEM space that further expands the applicability of our project to a large number of fields involved with modeling and simulation. For instance, the models used by circuit simulation, heat transfer, and structural mechanics can all be represented by very large sparse matrices. Accelerated sparse solvers will allow engineers to more quickly turn around designs with increased detail and accuracy. Large sparse matrices commonly arise in other fields involving statistics and optimization where a large amount number of elements have various interactions. For example, electrical power systems, traffic flow optimization, economics, search index rankings, and the modeling of chemical processes are just a small sample of fields where the interaction of a large number coupled elements are represented through sparse matrices. Accelerated sparse solvers and decompositions will allow scientists to rapidly study larger problems in less time.