Mission

The goal of  ASIC is to create a multi-site multidisciplinary consortium that explores research frontiers in emerging computing platforms for cognitive applications, offering unique value to members involved in the following four spheres of concentration:

graphic of ASIC missions

Defense Technology

  • aerospace, autonomous systems, anomaly detection, unmanned vehicles, surveillance

Information Technology

  • search, content discovery and recommendation, big data analytics

Infrastructure

  • microprocessors and accelerators, HPC solutions, computing platforms

Applications

  • medical and healthcare, diagnosis, circuit design, mobile devices, cyber-physical systems, communication, E-commerce

The above diagram illustrates the main operational areas of the ASIC center, in addition to the three member sites and their roles in technology development and applications. The ASIC center focuses on designing alternative computing platforms for cognitive applications, which perform inefficiently on conventional von Neumann architectures. The ASIC center is motivated by the recent rapid developments in technology related to cognitive applications, such as:

  • Applications of deep learning techniques have fundamentally changed the landscape of many industry sectors, especially the ones requiring learning capability of big data analytics and artificial intelligence.
  • Due to the rapid increase in the scale of the dataset being processed, hardware acceleration becomes extremely important in modern applications. Alternative computing platforms have changed from a complement to von Neumann platforms to a “must-have” and standalone technical solution.
  • Many “driving-horse” sectors of IT industry, e.g., mobile and cloud computing, start to migrate intelligence into their products and services. This trend generates many new opportunities for both hardware and software in the targeted areas of the ASIC with strong sustainability requirements.
  • The advances in alternative sustainable and intelligent computing techniques have enabled many new applications in bioinformation and healthcare that predict epidemics, cure diseases (e.g., cancer immunotherapy), improve quality of life, and avoid preventable deaths.