Memory Design Techniques for Low Energy Embedded Systems
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Delivery and Returns see our delivery rates and policies thinking of returning an item? See our Returns Policy. Visit our Help Pages. Audible Download Audio Books. Shopbop Designer Fashion Brands. Amazon Prime Music Stream millions of songs, ad-free. State-of-the-art circuit and system design methodologies from industry and academia will be elaborated to solve the spintronic memory limitations and expose the benefits.
The methods will include adaptive biasing, current boosting, data encoding, error-correction, trade-off with data retention etc. This section will conclude with applications of spintronics in new areas such as hardware security and non-Boolean computation models. The last part of this tutorial will describe another promising memory technology, namely RRAM, where the storage element is resistive in nature. We will cover device-circuit-architecture level design issues and solutions associated with application of RRAM to both storage as well as adaptive computing.
Typical RRAM cells suffer from high access power and poor sense margin.
Design techniques to lower the power consumption such as data encoding, write pause, and circuit-level solution for addressing the sneak path issue will be discussed to mitigate the power while maintaining required robustness. Multi-level RRAM, design challenges and solutions will also be described. We will cover applications of RRAM in the processor memory hierarchy as well as in efficient reconfigurable computing fabric. We will describe the challenges and opportunities in building RRAM based reconfigurable hardware - both purely spatial such as FPGA , as well as spatio-temporal.
For wide array of data-intensive applications, energy dissipation is primarily contributed by transportation of the data from off-chip memory to on-chip computing elements- a limitation referred to as the "Von-Neumann bottleneck".
- Сведения о продавце.
- Die heilende Kraft der Zahlen und Symbole: Universelle Energiequellen praktisch nutzen (German Edition).
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Finally, we will describe the opportunities of using RRAM in brain-inspired computing, e. The audiences will be able to takeaway following key points from this tutorial: Introduction and Motivation - 15 min a.
Need for embedded memory b. Static Random Access Memory - 50 min a.
Spintronic Memory - 50 min a. Resistive RAM - 50 min a. Conclusions and Discussions - 15 min a. Current industrial practices b. Swaroop Ghosh received his B.
Embedded system - Wikipedia
He joined the faculty of University of South Florida in Fall Ghosh was a senior research and development engineer in Advanced Design, Intel Corp from to At Intel, his research was focused on low power and robust embedded memory design in scaled technologies. He has filed seven US patents, published over 45 papers and authored a book chapter.
Ghosh is a senior member of IEEE. Swarup Bhunia received his B.