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Publications associées (117)

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Log-Free Concurrent Data Structures

Rachid Guerraoui, Aleksandar Dragojevic, Mihail Igor Zablotchi, Tudor Alexandru David

Non-volatile RAM (NVRAM) makes it possible for data structures to tolerate transient failures, assuming however that programmers have designed these structures such that their consistency is preserved upon recovery. Previous approaches are typically transa ...

USENIX ASSOC2018

Mixed-precision architecture based on computational memory for training deep neural networks

Irem Boybat Kara, Evangelos Eleftheriou, Abu Sebastian

Deep neural networks (DNN) have revolutionized the field of machine learning by providing unprecedented human-like performance in solving many real-world problems such as image or speech recognition. Training of large DNNs, however, is a computationally in ...

IEEE2018

3D Bpconvnet To Reconstruct Parallel Mri

Michaël Unser, Kyong Hwan Jin

In recent years, compressed sensing techniques have been applied to the reconstruction of parallel magnetic resonance (MR) images. Particularly for 3D MR signal, it is crucial to acquire fewer samples to reduce the distortions caused by long-time acquisiti ...

IEEE2018

Universally Scalable Concurrent Data Structures

Tudor Alexandru David

The increase in the number of cores in processors has been an important trend over the past decade. In order to be able to efficiently use such architectures, modern software must be scalable: performance should increase proportionally to the number of all ...

EPFL2017

BLOCK: Efficient Execution of Spatial Range Queries in Main-Memory

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed, Matthaios Alexandros Olma

The execution of spatial range queries is at the core of many applications, particularly in the simulation sciences but also in many other domains. Although main memory in desktop and supercomputers alike has grown considerably in recent years, most spatia ...

2017

BLOCK: Efficient Execution of Spatial Range Queries in Main-Memory

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed, Matthaios Alexandros Olma

ACM New York, NY, USA2017

Efficient Adaptive Hard Real-time Multi-processor Systems

Stefanos Skalistis

Modern computing systems are based on multi-processor systems, i.e. multiple cores on the same chip. Hard real-time systems are required to perform particular tasks within certain amount of time; failure to do so characterises an unaccepted behavior. Hard ...

EPFL2017

Near-Memory Data Services

Babak Falsafi

This column introduces seven invited position papers about the challenges and opportunities in near-data processing. "Near-Memory Data Services" by Babak Falsafi, "Automata Processing: The Memory Is the Processor!" by Mircea Stan, Kevin Skadron, "Overcomin ...

Institute of Electrical and Electronics Engineers2016

Scaling Up Concurrent Analytical Workloads on Multi-Core Servers

Iraklis Psaroudakis

Today, an ever-increasing number of researchers, businesses, and data scientists collect and analyze massive amounts of data in database systems. The database system needs to process the resulting highly concurrent analytical workloads by exploiting modern ...

EPFL2016

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