Application-Specific Computing Architectures and Systems

Course Dates and Time

Date: 04.10.2017 - 08.12.2017; Twice a week (i.e., on Wednesdays and Fridays), Time: 14:00 - 16:00; Location: Seminarraum Techn. Informatik [Institutsgebäude (Treitlstraße 3) - Zugang über Operngasse 9 (Erdgeschoß) ]


  • Semesterwochenstunden: 2.0
  • ECTS: 3.0
  • Typ: VU Vorlesung mit Übung



  • Learning basics of application-specific computing systems and architectures.
  • Understanding different characterization of image/video processing algorithms requiring application-specific architectures and design constraints.
  • Learning the interplay of application-specific architectures and run-time management techniques for high power/energy efficiency or performance-per-power efficiency.
  • Access to modern architectural trends and corresponding research themes.
  • Ability to design, develop, and apply concepts to real-world applications of camera-based processing systems.


Application-Specific Computing Systems are ubiquitous, ranging from Internet-of-Things, Automotive, Medical Imaging, Security, Consumer, etc. The continuously increasing user demands have resulted in a significant growth of advanced computing architectures and systems, which has been well complemented by the technological growth steered by Moore¿s law. Moreover, algorithmic complexities and data rates are also ramping up as the application use cases are becoming more and more sophisticated. An excellent example would be a multi-camera system where, on the one hand video resolutions have increased to Ultra High-Definition and Super-Vision Multi-View Processing which requires massive data rate processing, and on the other hand, these computing architectures are subjected to stringent design constraints in terms of power, energy and area. Therefore, designing such application-specific architectures for high energy efficiency is a significant challenge.

This lecture aims at providing (1) an overview of application-specific architecture and commercial design tools; and (2) an insight on innovative architectures and run-time systems for highly energy-efficient application-specific computing systems. A key focus will be on hardware-software collaborative techniques and how to identify important application-specific characteristics to optimize and adapt underlying computing architectures (that provide the computation capabilities), and even the executing algorithms (that determine the computation requirements). The techniques and concepts will be explained with the help of real-world applications of embedded image and video processing, which have widely proliferated in our daily life.

In this lecture, the following topics will be explained along with a perspective to the actual research works and practical applications to real-world application-specific systems:

  • Introduction of application-specific computing architectures
  • Analysis of application-specific properties with respect to algorithms' performance, power, and memory requirements
  • State-of-the-art techniques and commercial design tools for application-specific systems.
  • Complexity reduction techniques.
  • Advanced trends for application-specific (multi-/many-core) processor architectures and design methods
  • Advanced on-chip memory architectures and application-specific optimizations and management.
  • Run-time systems for efficient application-driven resource and power management
  • Emerging trends for application-driven extreme energy-efficiency, like Approximate Computing and Deep Learning.


Prof. Dr. Muhammad Shafique


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