IEEE Design&Test Vol. 38, Issue 6
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Speaker:
Special Issue on Stochastic Computing for Neuromorphic Applications
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- Date: November/December
Magazine
Volume 38, Issue 6 (November/December)
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Highlights
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November/December 2021 Content
From the EIC
| • | Stochastic Computing for Neuromorphic Applications |
| View full article (PDF). |
Special Issue on Cross-Layer Design of Cyber–Physical Systems
| • | Guest Editors’ Introduction: Introduction: Stochastic Computing for Neuromorphic Applications |
| View full article (PDF). |
| • | A Conceptual Framework for Stochastic Neuromorphic Computing |
| This keynote article is written by Brian Gaines, the inventor of stochastic computing. He shares both a view back on the history of neuromorphic computing and a view forward on deep learning as a new information processing technology. read more View full article (PDF). |
| • | Embracing Stochasticity to Enable Neuromorphic Computing at the Edge |
| his article discusses emerging nano-devices—resistive RAMs and spintronics—and their use in future neuromorphic systems. read more. View full article (PDF). |
| • | Exact Stochastic Computing Multiplication in Memristive Memory |
| This article focuses on memristive nano-devices and their use for stochastic computing (SC). It demonstrates how to convert numbers between binary and stochastic domains and how to perform multiplications using inmemory computations by the memristive logic family “MAGIC.” read more. View full article (PDF). |
| • | Training Binarized Neural Networks Using Ternary Multipliers |
| This article considers the under-investigated problem of training neural networks based on stochastic computing. read more. View full article (PDF). |
| • | In-Stream Correlation-Based Division and Bit-Inserting Square Root in Stochastic Computing |
| This article presents improved stochastic computing primitives for division and square root operations. Both are nonlinear functions that cannot be reduced to additions and multiplications. read more View full article (PDF). |
| • | High-Performance Deterministic Stochastic Computing Using Residue Number System |
| This article discusses how to reduce the latency of stochastic computations. The authors represent an integer number as a set of remainders with respect to a set of relatively prime moduli. read more View full article (PDF). |
| • | An Area- and Power-Efficient Stochastic Number Generator for Bayesian Sensor Fusion Circuits |
| This article introduces a new stochastic number generator module with low autocorrelation properties. read more View full article (PDF). |
Keynote Papers
| • | The Emerging Majority: Technology and Design for Superconducting Electronics |
| Emerging computing technologies will enable design of energy-efficient circuits and systems in the future. read more View full article (PDF). |
General Interest Papers
| • | Energy-Efficient and Error-Resilient Cognitive I/O for 3-D-Integrated Manycore Microprocessor |
| This article presents a novel framework that combines a QoS-aware memory partitioning scheme and a reinforcement-learning-based I/O voltage-swing tuning for energy-efficient and reliable processor-DRAM subsystem design. read more View full article (PDF). |
Departments
| • | The Last Byte: Computing in the Real World |
| View full article (PDF). |
