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The opinions, findings, and conclusions or recommendations expressed are those of the Center author(s) and do not necessarily reflect the views of the National Science Foundation.
Center Overview
The Center for Alternative Sustainable and Intelligent Computing (ASIC) focuses on designing alternative computing platforms for cognitive applications that perform inefficiently on conventional von Neumann architectures. ASIC is motivated by the recent rapid developments in technology related to cognitive applications, and aims to enable high performance and energy-efficient machine intelligence through novel hardware circuits, architecture design, and optimized computation models.
Center Personnel
Yiyu Shi
Center Staff
+1 574 631 7432
yshi4@nd.edu
Yiran Chen
Center Staff
+1 919 684 3030
yiran.chen@duke.edu
Qinru Qiu
Center Staff
+1 315 443 2807
qiqiu@syr.edu
Research Focus
Defense technology research includes:
- Aerospace.
- Anomaly detection.
- Autonomous systems.
- Surveillance.
- Unmanned vehicles.
Awards
Neuromorphic circuits, which mimic the human brain's structure and processing ability on silicon, promise to enable ultralow power, high performance computing. Various key breakthroughs have emerged from exponential advances in computing technology and understanding brains, with increasing interest from governments, research institutes, and business entities. Nonetheless, existing computing architectures can hardly demonstrate universal advantages in a large variety of neuromorphic computing tasks. To address this challenge, this project will build the Center of Alternative Sustainable and Intelligent Computing (ASIC). ASIC is a collaborative industry-university partnership that joins leading industry members with academic researchers to conduct multidisciplinary science and research to enable high performance and energy efficient machine intelligence through novel circuits, architecture, and computation models.
The Center of Alternative Sustainable and Intelligent Computing (ASIC) focuses on alternative computing platforms for cognitive applications, which are in general difficult to be efficiently performed on conventional von Neumann architecture. At Syracuse University (SU), the ASIC-SU site focuses on hardware oriented software and algorithm developments for cognitive applications, with an emphasis on autonomous systems, surveillance and unmanned aerial vehicle (UAV) technologies. The establishment of ASIC accelerates the development of new computing paradigms in industry sectors and expedites technology transfer from research discoveries to practical solutions.
ASIC research will have broad impact on the computer and IT industries by introducing alternative computing platforms that complement the conventional computing platforms built on von Neumann architectures in the short term, and position alternative sustainable and intelligent computing equivalents important in long term. The knowledge and expertise developed via ASIC will effectively enable the predicted boom in cognitive applications and their urgent demands for hardware and software support. The talent and expertise of center PIs and the industry partners are integrated to enhance the competence of the center members and accelerate technology transfer.
ASIC research may involve academic and industrial data along with public domain data. This data and the resulting research outputs will be maintained using appropriate best practices for each type of data for a period of three years after the closing of ASIC. A central repository, suitably tagged for appropriate referencing and documentation, will be set up at https://asic.pratt.duke.edu for maintaining the acquired and generated data from center projects. Access to all models and project results will be stored online and made available for downloading in near real time to respond to approved user requests.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Read More >
Neuromorphic circuits, which mimic the human brain's structure and processing ability on silicon, promise to enable ultralow power, high performance computing. Various key breakthroughs have emerged from exponential advances in computing technology and understanding brains, with increasing interest from governments, research institutes, and business entities. Nonetheless, existing computing architectures can hardly demonstrate universal advantages in a large variety of neuromorphic computing tasks. To address this challenge, this project will build the Center of Alternative Sustainable and Intelligent Computing (ASIC). ASIC is a collaborative industry-university partnership that joins leading industry members with academic researchers to conduct multidisciplinary science and research to enable high performance and energy efficient machine intelligence through novel circuits, architecture, and computation models.
The Center of Alternative Sustainable and Intelligent Computing (ASIC) focuses on alternative computing platforms for cognitive applications, which are in general difficult to be efficiently performed on conventional von Neumann architecture. The ASIC Notre Dame (ASIC-ND) site will focus primarily on neuromorphic computing platforms for telemedicine and healthcare related applications, by leveraging the strong research background and the long-term collaboration with Indiana University School of Medicine and relevant industry sectors. The establishment of ASIC is expected to accelerate the development of new computing diagrams in industry sectors and expedites technology transfer from research discoveries to practical solutions.
ASIC research will have broad impact on the computer and IT industries by introducing alternative computing platforms that complement the conventional computing platforms built on von Neumann architectures in the short term, and position alternative sustainable and intelligent computing equivalents important in long term. The knowledge and expertise developed via ASIC will effectively enable the predicted boom in cognitive applications and their urgent demands for hardware and software support. The talent and expertise of center PIs and the industry partners are integrated to enhance the competence of the center members and accelerate technology transfer.
ASIC research may involve academic and industrial data along with public domain data. This data and the resulting research outputs will be maintained using appropriate best practices for each type of data for a period of three years after the closing of ASIC. A central repository, suitably tagged for appropriate referencing and documentation, will be set up at https://asic.pratt.duke.edu for maintaining the acquired and generated data from center projects. Access to all models and project results will be stored online and made available for downloading in near real time to respond to approved user requests.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Read More >
Neuromorphic circuits, which mimic the human brain's structure and processing ability on silicon, promise to enable ultralow power, high performance computing. Various key breakthroughs have emerged from exponential advances in computing technology and understanding brains, with increasing interest from governments, research institutes, and business entities. Nonetheless, existing computing architectures can hardly demonstrate universal advantages in a large variety of neuromorphic computing tasks. To address this challenge, this project will build the Center of Alternative Sustainable and Intelligent Computing (ASIC). ASIC is a collaborative industry-university partnership that joins leading industry members with academic researchers to conduct multidisciplinary science and research to enable high performance and energy efficient machine intelligence through novel circuits, architecture, and computation models.
The Center of Alternative Sustainable and Intelligent Computing (ASIC) focuses on alternative computing platforms for cognitive applications, which are in general difficult to be efficiently performed on conventional von Neumann architecture. The ASIC Duke University (ASIC-Duke) Site will serve as the lead Site for ASIC and will lead the coordination and management of the Center. Research at the ASIC Duke Site will focus on industry-driven hardware innovations, especially infrastructure and implementation. The establishment of ASIC is expected to accelerate the development of new computing diagrams in industry sectors and expedites technology transfer from research discoveries to practical solutions.
ASIC research will have broad impact on the computer and IT industries by introducing alternative computing platforms that complement the conventional computing platforms built on von Neumann architectures in the short term, and position alternative sustainable and intelligent computing equivalents important in long term. The knowledge and expertise developed via ASIC will effectively enable the predicted boom in cognitive applications and their urgent demands for hardware and software support. The talent and expertise of center PIs and the industry partners are integrated to enhance the competence of the center members and accelerate technology transfer.
ASIC research may involve academic and industrial data along with public domain data. This data and the resulting research outputs will be maintained using appropriate best practices for each type of data for a period of three years after the closing of ASIC. A central repository, suitably tagged for appropriate referencing and documentation, will be set up at https://asic.pratt.duke.edu for maintaining the acquired and generated data from center projects. Access to all models and project results will be stored online and made available for downloading in near real time to respond to approved user requests.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Read More >