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End to End System Design for DRAM-based TRNG


Research paper titled "DR-STRaNGe: End-to-End System Design for DRAM-based True Random Number Generators" is presented from researchers at TOBB University of Economics and Technology and ETH Zurich. Abstract "Random number generation is an important task in a wide variety of critical applications including cryptographic algorithms, scientific simulations, and industrial testing tools. True ... » read more

Neuromorphic Chips & Power Demands


Research paper titled "A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware," from researchers at Graz University of Technology and Intel Labs. Abstract "Spike-based neuromorphic hardware holds the promise to provide more energy efficient implementations of Deep Neural Networks (DNNs) than standard hardware such as GPUs. But this requires to understand how D... » read more

DarkGates: A Hybrid Power-Gating Architecture to Mitigate the Performance Impact of Dark-Silicon in High Performance Processors


New research paper from ETH Zurich and others. Abstract "To reduce the leakage power of inactive (dark) silicon components, modern processor systems shut-off these components' power supply using low-leakage transistors, called power-gates. Unfortunately, power-gates increase the system's power-delivery impedance and voltage guardband, limiting the system's maximum attainable voltage (i.e., ... » read more

LoRaWAN End Nodes: Security and Energy Efficiency Analysis


New academic research paper from University of Sarajevo and Technical University of Ostrava. Abstract: "With the development of electronics and communication techniques, the interest in realizing sensor networks with a large number of end nodes is growing. The main idea is to install devices in remote locations without direct supervision, which requires an uninterrupted power supply and sec... » read more

An Energy-Efficient DRAM Cache Architecture for Mobile Platforms With PCM-Based Main Memory


Abstract "A long battery life is a first-class design objective for mobile devices, and main memory accounts for a major portion of total energy consumption. Moreover, the energy consumption from memory is expected to increase further with ever-growing demands for bandwidth and capacity. A hybrid memory system with both DRAM and PCM can be an attractive solution to provide additional capacity ... » read more

Towards Decarbonization: Keeping Electronics Energy Consumption In Check


The International Technology Roadmap for Semiconductors (ITRS) roadmap famously said in 2001 that "cost of design is the greatest threat to the continuation of the semiconductor roadmap." For years, the industry followed the ITRS updates on productivity improvements provided by automating design and hardware to counteract the looming design cost. The discussion on decarbonization has some simil... » read more

Is AI Good Or Bad For The Planet?


Will artificial intelligence save or sink planet earth? We’re surrounded by AI. When you use the internet, take a photo, use predictive text, or watch TV, you are interacting with AI. And we are still in the early stages of this revolution in technology and our lives. But AI can require large amounts of power. Researchers have documented the astounding amount of power required to train ... » read more

Revealing DRAM Operating GuardBands through Workload-Aware Error Predictive Modeling


Abstract Abstract—Improving the energy efficiency of DRAMs becomes very challenging due to the growing demand for storage capacity and failures induced by the manufacturing process. To protect against failures, vendors adopt conservative margins in the refresh period and supply voltage. Previously, it was shown that these margins are too pessimistic and will become impractical due to high ... » read more

Data Center Hyperscaling


As we move in to 2020 it’s clear that every sector of industry, including the semiconductor industry, will have a responsibility to address growing environmental concerns. We should be aware that as our sector underpins the growth in AI, 5G telecommunications, crypto-currency and high performance compute applications, it is predicted that by 2030 energy consumption attributable to data center... » read more

Understanding the Interactions of Workloads and DRAM Types: A Comprehensive Experimental Study


Abstract "It has become increasingly difficult to understand the complex interaction between modern applications and main memory, composed of DRAM chips. Manufacturers are now selling and proposing many different types of DRAM, with each DRAM type catering to different needs (e.g., high throughput, low power, high memory density). At the same time, the memory access patterns of prevalent and... » read more

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