Wednesday, February 24, 2021
IBM Analog Hardware Acceleration Kit:
A Flexible and Fast PyTorch Toolkit for Simulating ANN Training and Inference on Resistive Crossbar Arrays
Memristive crossbar arrays are a promising future technology for accelerating AI workloads, but noise and non-idealities demand for improved algorithmic solutions. We introduce the IBM Analog Hardware Acceleration Kit, a first of a kind open source toolkit to simulate crossbar arrays from within PyTorch, to conveniently estimate the impact of material properties and non-idealities on the accuracy for arbitrary ANNs.
Speaker: Malte Rasch, IBM
Explore
III-Nitride Ferroelectrics for Integrated Low-Power and Extreme-Environment Memory
Monday, May 5, 2025 | 4:00 - 5:00pm ET
Hybrid
Zoom & MIT Campus
New Electronic “skin” could Enable Lightweight Night-vision Glasses
Jennifer Chu | MIT News
MIT engineers developed ultrathin electronic films that sense heat and other signals, and could reduce the bulk of conventional goggles and scopes.
MIT Engineers Print Synthetic “Metamaterials” that are Both Strong and Stretchy
Jennifer Chu | MIT News
A new method could enable stretchable ceramics, glass, and metals, for tear-proof textiles or stretchy semiconductors.