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Publications associées (322)

Material and Electrical study of HfO2-Based Resistive Random Access Memories (ReRAMs)

Resistive Random Access Memories (ReRAMs) have been researched intensively in the last past decades as a promising alternatives technology for the next-generation non-volatile memory (NVM) devices. ReRAMâs excellent performance properties such as high sw ...

EPFL2019

Performance Contracts for Software Network Functions

George Candea, Solal Vincenzo Pirelli, Arseniy Zaostrovnykh, Rishabh Ramesh Iyer, Luis David Figueiredo Mascarenhas Moreira Pedrosa

Software network functions (NFs), or middleboxes, promise flexibility and easy deployment of network services but face the serious challenge of unexpected performance behaviour. We propose the notion of a performance contract, a construct formulated in ter ...

USENIX ASSOC2019

Power Analysis Resilient SRAM Design Implemented with a 1% Area Overhead Impedance Randomization Unit for Security Applications

Robert Giterman

Power analysis attacks are an effective tool to extract sensitive information using side-channel analysis, forming a serious threat to IoT systems-on-a-chip (SoCs). Embedded memories implemented with conventional 6T SRAM macrocells often dominate the area ...

IEEE2019

A Real-Time Multi-Camera Depth Estimation ASIC with Custom On-Chip Embedded DRAM

Jonathan Emmanuel D Narinx

The capability to process high-resolution videos in real-time is becoming more important in a wide variety of applications such as autonomous vehicles, virtual reality or intelligent surveillance systems. The high-accuracy and complex video processing algo ...

EPFL2019

FPGA-Assisted Deterministic Routing for FPGAs

Mirjana Stojilovic, Dario Korolija

FPGA routing is one of the most time-consuming steps of FPGA compilation, often preventing fast edit-compile-test cycles in prototyping and development. There have been attempts to accelerate FPGA routing using algorithmic improvements, multi-core or multi ...

2019

GC-eDRAM With Body-Bias Compensated Readout and Error Detection in 28-nm FD-SOI

Andreas Peter Burg, Adam Shmuel Teman, Robert Giterman, Andrea Bonetti

Gain-cell embedded DRAM (GC-eDRAM) is an attractive alternative to conventional SRAM due to its high-density, low-leakage, and inherent two-ported functionality. However, its dynamic storage mechanism requires power-hungry refresh cycles to maintain data. ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Pythia: Remote Oracles for the Masses

Mathias Josef Payer, Yuqing Zhang

Remote Direct Memory Access (RDMA) is a technology that allows direct access from the network to a machine's main memory without involving its CPU. RDMA offers low-latency, high-bandwidth performance and low CPU utilization. While RDMA provides massive per ...

USENIX ASSOC2019

Impact of Memory Voltage Scaling on Accuracy and Resilience of Deep Learning Based Edge Devices

David Atienza Alonso, Andreas Peter Burg, Miguel Peon Quiros, Andrea Bonetti, Martino Ruggiero, Benoît Walter Denkinger, Flavio Ponzina, Soumya Subhra Basu, Szabolcs Balási

Energy consumption is a significant obstacle to integrate deep learning into edge devices. Two common techniques to curve it are quantization, which reduces the size of the memories (static energy) and the number of accesses (dynamic energy), and voltage s ...

2019

Shrink It or Shed It! Minimize the Use of LSQs in Dataflow Designs

Paolo Ienne, Andrea Guerrieri, Lana Josipovic, Atri Bhattacharyya

When applications have unpredictable memory accesses or irregular control flow, dataflow circuits overcome the limitations of statically scheduled high-level synthesis (HLS). If memory dependences cannot be determined at compile time, dataflow circuits rel ...

IEEE COMPUTER SOC2019

An Associativity-Agnostic in-Cache Computing Architecture Optimized for Multiplication

David Atienza Alonso, Marina Zapater Sancho, Alexandre Sébastien Julien Levisse, Marco Antonio Rios, William Andrew Simon

With the spread of cloud services and Internet of Things concept, there is a popularization of machine learning and artificial intelligence based analytics in our everyday life. However, an efficient deployment of these data-intensive services requires per ...

2019

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