Tag Archives: computing

NEW PAPER: A golden age for computing frontiers, a dark age for computing education?

Paper: https://doi.org/10.1145/3457388.3458673 

Abstract: There is no doubt that the body of knowledge spanned by the computing disciplines has gone through an unprecedented expansion, both in depth and breadth, over the last century. In this position paper, we argue that this expansion has led to a crisis in computing education: quite literally the vast majority of the topics of interest of this conference are not taught at the undergraduate level and most graduate courses will only scratch the surface of a few selected topics. But alas, industry is increasingly expecting students to be familiar with emerging topics, such as neuromorphic, probabilistic, and quantum computing, AI, and deep learning. We provide evidence for the rapid growth of emerging topics, highlight the decline of traditional areas, muse about the failure of higher education to adapt quickly, and delineate possible ways to avert the crisis by looking at how the field of physics dealt with significant expansions over the last centuries.

Presentation: https://youtu.be/gjw9dRWaeNM

Citation: C. Teuscher, “A golden age for computing frontiers, a dark age for computing education?” In Proceedings of the 18th ACM International Conference on Computing Frontiers (CF ’21). Association for Computing Machinery, New York, NY, USA, 140–143, 2021. DOI: https://doi.org/10.1145/3457388.3458673

Paper acceptance rate: 25%

 

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New paper: Deep reservoir computing with memcapacitors

S. J. Dat Tran and C. Teuscher, “Deep Memcapacitive Network,” 2020 IEEE 15th International Conference on Nano/Micro Engineered and Molecular System (NEMS), San Diego, CA, USA, 2020, pp. 200-205, doi: https://doi.org/10.1109/NEMS50311.2020.9265561

 

CFP: Special Section on Parallel and Distributed Computing Techniques for Non-Von Neumann Technologies

Call for Papers: Special Section on Parallel and Distributed Computing Techniques for Non-Von Neumann Technologies

Traditional computing is heading increasingly into the memory wall, the power wall, the instruction-level-parallelism wall, and other performance limiters. This situation presents new opportunities for non-traditional computer architectures—neuromorphic, quantum, in-memory, and other approaches not based on the von Neumann architecture—to deliver the perpetually needed improvements in execution speed. For this special section of the IEEE Transactions on Parallel and Distributed Systems (TPDS), we will be accumulating recent community research in these areas, with a specific focus on parallel and distributed computing architectures, into a curated selection of articles.

About TPDS special sections

TPDS has recently started a new initiative called “special sections.” Compared with regular submissions to TPDS, special sections have some differences: (1) submissions are focused on special topics of interest (similar to special issues); (2) special sections have fixed deadlines for submission and notifications; and (3) special sections have a standing committee of reviewers similar to conferences. This is the second such special section that we are planning.

Topics of interest

The special section is dedicated to novel, emerging, and promising parallel and distributed computing techniques for non-von Neumann technologies. This includes all manner of radical new architectures, but not conventional accelerators, such as GPUs, FPGAs, and SIMD systems or ordinary CPUs embedded in various devices. Articles about software simulations and foundational models of such systems are welcome, but novel programming models designed for conventional hardware are likely to be deemed out of scope. Topics of interest include but are not limited to:

  • Neuromorphic computing
  • Biologically-inspired computing
  • Quantum computing
  • Annealing-based computing, both quantum and classical
  • Memristor- and other emerging-device-based computing
  • Approximate, probabilistic, and inexact computing
  • In-memory processing and memory-based computing
  • Analog computing
  • Reversible computing
  • DNA computing
  • Thermodynamic computing
  • Optical computing
  • Chemical computing and chemical reaction networks
  • Cellular computing
  • Collision-based computing

Submission deadline: Sep 1, 2020

More info at https://www.computer.org/digital-library/journals/td/call-for-papers-special-section-on-parallel-and-distributed-computing-techniques-for-non-von-neumann-technologies