AxC23: 8th Workshop on Approximate Computing
Nowadays, Approximate Computing (AxC) represents a novel design paradigm for building modern systems, which offer trade-offs between efficiency in terms of performance, power consumption, hardware area, execution timing, and the quality/exactness of the outcomes. AxC is based on the intuitive observation that, while performing exact computation requires a high number of computational resources, allowing a selective approximation or an occasional relaxation of the specification may provide significant gains in energy efficiency while still providing acceptable results. Moreover, while the hidden cost of AxC reduces an application’s inherent resiliency to errors, AxC has also recently been demonstrated to be effective in safety-critical applications.
The DSN Workshop on Approximate Computing explores the AxC continuum, allowing new methodologies to exploit the approximation in many recent application domains, such as machine learning, safety, and security, in an effective, dependable, and secure manner. There is a lack of methodologies and automated tools for the entire design and manufacturing flow, while professionals are already working on real systems deploying AxC solutions. Moreover, existing and new techniques are moving across all system layers, focusing not only on the hardware layer anymore but including cross-layer approaches, broadening the potential community of interested researchers.
The workshop is open for researchers and professionals to present and discuss novel ideas and techniques for approximation across all layers of the system stack. This edition puts an extra focus on cross-layer approximate computing and approximation techniques for open architectures, with particular emphasis on the EU microprocessor plan.
This year’s (in person) event will be in conjunction with
Conference on Dependable Systems and Networks (DSN2023)
- Submission deadline : March 28th, 2023
- Notification of acceptance: April 21st, 2023
- Camera ready: May 5th, 2023
The Workshop accepts Extended Abstract submissions (of at most four pages).
The authors can submit an extended abstract (2 pages + references)
A short paper of up to 4 pages.
The four page limit includes references. Accepted papers will be published in the DSN supplemental volume and made available in IEEE Xplore.
Each submission has to be in a standard IEEE format.
Submit your papers to the workshop track of DSN via easychair:
Choose workshops in the submissions bar. You will be redirected to easychair, or go directly to https://easychair.org/my/conference?conf=dsn2023
After you login to easychair as an author, choose the Track "8th Workshop on Approximate Computing”
Alexandra Kourfali - Stuttgart University (DE)
Alessandro Savino - Politecnico di Torino (IT)
Jorge Castro-Godínez - Costa Rica Institute of Technology (CR)
|Jie Han||U. Alberta (CA)|
|Sybille Hellebrand||Paderborn U (DE)|
|Jörg Henkel||KIT (DE)|
|Anand Raghunathan||Purdue U (USA)|
|Kaushik Roy||Purdue U (USA)|
|Adit Singh||Auburn U (USA)|
|Hans-Joachim Wunderlich||Stuttgart U (DE)|