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Near-Memory Data Services

Publications associées (33)

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All-memristive neuromorphic computing with level-tuned neurons

Stanislaw Andrzej Wozniak, Evangelos Eleftheriou, Angeliki Pantazi

In the new era of cognitive computing, systems will be able to learn and interact with the environment in ways that will drastically enhance the capabilities of current processors, especially in extracting knowledge from vast amount of data obtained from m ...

Iop Publishing Ltd2016

HRL: Efficient and Flexible Reconfigurable Logic for Near-Data Processing

Christos Kozyrakis

The energy constraints due to the end of Dennard scaling, the popularity of in-memory analytics, and the advances in 3D integration technology have led to renewed interest in near-data processing (NDP) architectures that move processing closer to main memo ...

Ieee2016

Automatic Generation of Efficient Accelerators for Reconfigurable Hardware

Christos Kozyrakis, Yunqi Zhang

Acceleration in the form of customized datapaths offer large performance and energy improvements over general purpose processors. Reconfigurable fabrics such as FPGAs are gaining popularity for use in implementing application-specific accelerators, thereby ...

Ieee2016

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In recent years, neural network accelerators have been shown to achieve both high energy efficiency and high performance for a broad application scope within the important category of recognition and mining applications. Still, both the energy efficiency a ...

ACM2015

Exploiting NVM in Large-scale Graph Analytics

Willy Zwaenepoel, Jasmina Malicevic

Data center applications like graph analytics require servers with ever larger memory capacities. DRAM scaling, how- ever, is not able to match the increasing demands for ca- pacity. Emerging byte-addressable, non-volatile memory technologies (NVM) offer a ...

2015

Accelerating Thermal Simulations of 3D ICs with Liquid Cooling using Neural Networks

David Atienza Alonso, Arvind Raj Mahankali Sridhar, Martino Ruggiero, Alessandro Vincenzi

Vertical integration is a promising solution to further increase the performance of future ICs, but such 3D ICs present complex thermal issues that cannot be solved by conventional cooling techniques. Interlayer liquid cooling has been proposed to extract ...

ACM2012

The main aim of this thesis is to examine the advantages of 3D stacking applied to microprocessors and related integrated microprocessor systems in the architectural level. In the succession of years microprocessors are aiming towards lower power consumpti ...

EPFL2012

Molecular associative memory: An associative memory framework with exponential storage capacity for DNA computing

Mohammad Amin Shokrollahi, Krishna Kumar, Amir Hesam Salavati

Associative memory problem: Find the closest stored vector (in Hamming distance) to a given query vector. There are different ways to implement an associative memory, including the neural networks and DNA strands. Using neural networks, connection weights ...

2011

Evolutionary Advantages of Neuromodulated Plasticity in Dynamic, Reward- based Scenarios

Dario Floreano, Claudio Mattiussi, Peter Dürr, Andrea Soltoggio

memory in biological neural networks. Similarly, artificial neural networks could benefit from modulatory dynamics when facing certain types of learning problem. Here we test this hypothesis by introducing modulatory neurons to enhance or dampen neural pla ...

MIT Press2008

Because the market has an insatiable appetite for new functionality, performance is becoming an increasingly important factor. The telecommunication and network domains are especially touched by this phenomenon but they are not the only ones. For instance, ...

EPFL2007