computation

Advances in Microelectromechanical Digital Circuit Design: Low Power Computation, Sensing and Beyond

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KAUST

Electromechanical switches were the core elements of the very first digital computers in early 20th century. While these switches were later replaced by the smaller, faster and more reliable "transistor" technology, they found a new life following the development of nanofabrication tools and Micro-electromechannical Systems (MEMS). In this seminar we will explore the most recent advances in the field of MEMS-based digital circuit and sensor design. We also examine the application of MEMS switches and resonators in building the most important blocks of a digital system, namely adders, multipliers, data converters, sequential and combinational complex logic, and discuss the future of this technology in the beyond-CMOS era.

Efficient Computation Through Tuned Approximation

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B9 L2 R2322 H1

Numerical software is being reinvented to provide opportunities to tune dynamically the accuracy of computation to the requirements of the application, resulting in savings of memory, time, and energy. Floating point computation in science and engineering has a history of “oversolving” relative to expectations for many models. So often are real datatypes defaulted to double precision that GPUs did not gain wide acceptance until they provided in hardware operations not required in their original domain of graphics. However, computational science is now reverting to employ lower precision arithmetic where possible. Many matrix operations considered at a blockwise level allow for lower precision and many blocks can be approximated with low rank near equivalents.

Simulating evolution to understand a hidden switch

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Some organisms evolve an internal switch that can remain hidden for generations until stress flicks it on.

CovMT: Tracking virus mutations across the world

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An interactive platform helps users visualize where SARS-CoV-2 mutations start, how wide they spread and how infectious they are.

Cloud simulations get a dose of realism

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A focus on the fundamental physics of cloud formation leads to highly realistic simulations of different types of clouds.

Brain-on-a-chip would need little training

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A neural network that mimics the biology of the brain can be loaded onto a microchip for faster and more efficient artificial intelligence.