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Guest Editorial

Protecting Caches from Soft Errors

Soft error is one of the most important design concerns in modern embedded systems with aggressive technology scaling. Among various microarchitectural components in a processor, cache is the most susceptible component to soft errors. Error detection and correction codes are common protection techniques for cache memory due to their design... (more)

A Novel Method for Online Detection of Faults Affecting Execution-Time in Multicore-Based Systems

This article proposes a bounded interference method, based on statistical evaluations, for online... (more)

Analyzing the Fault Injection Sensitivity of Secure Embedded Software

Fault attacks on cryptographic software use faulty ciphertext to reverse engineer the secret... (more)

Area, Throughput, and Power Trade-Offs for FPGA- and ASIC-Based Execution Stream Compression

An emerging trend in safety-critical computer system design is the use of compression—for example, using cyclic redundancy check (CRC) or... (more)

Formal Model-Based Synthesis of Application-Specific Static RTOS

In an embedded system, the specialization of the code of the real-time operating system (RTOS) according to the requirements of the application allows... (more)

The Design and Implementation of the Synchronous Language CÉU

CéU is a synchronous language targeting soft real-time systems. It is inspired by Esterel and has a simple semantics with fine-grain control... (more)

The Perfect Getaway

The use of a managed, type-safe language such as Java in real-time and embedded systems offers productivity and, in particular, safety and dependability benefits at a reasonable cost. It has been shown for commodity systems that Escape Analysis (EA) enables a set of useful optimizations, and benefits from the properties of a type-safe language. In... (more)

PMC

We propose a novel approach to schedule memory requests in Mixed Criticality Systems (MCS). This approach supports an arbitrary number of criticality levels by enabling the MCS designer to specify memory requirements per task. It retains locality within large-size requests to satisfy memory requirements of all tasks. To achieve this target, we... (more)

Harmonicity-Aware Task Partitioning for Fixed Priority Scheduling of Probabilistic Real-Time Tasks on Multi-Core Platforms

The uncertainty due to performance variations of IC chips and resource sharing on multi-core... (more)

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About TECS 

The design of embedded computing systems, both the software and hardware, increasingly relies on sophisticated algorithms, analytical models, and methodologies. ACM Transactions on Embedded Computing Systems (TECS) aims to present the leading work relating to the analysis, design, behavior, and experience with embedded computing systems. 

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TECS Editor-in-Chief featured in "People of ACM"

Sandeep K. Shukla was recently reappointed as Editor-in-Chief of ACM Transactions on Embedded Computing Systems (TECS), and he was featured in the periodic series "People of ACM".  Full article.

Forthcoming Articles

Fixed-Priority Scheduling for Two-Phase Mixed-Criticality Systems

Editorial: Security of Mobile Devices

Exploiting Sparsity to Accelerate Fully Connected Layers of CNN-based Applications on Mobile SoCs

Convolutional neural networks (CNNs) are widely employed in many image recognition applications. The ever-increasing computational capability of mobile processors provides opportunities to run such applications in an energy efficient and low latency manner, and is therefore critical that they are properly optimized on these platforms. Matrix multiplication is an important operation used in CNNs. In this paper, we propose customized versions of the matrix multiplication algorithms that can help to speed up CNNs. Specifically, we propose a BCSC (Block Compressed Sparse Column) algorithm and a bitrepresentation based algorithm (BitsGEMM) that exploit sparsity to accelerate CNNs on the NVIDIA Jetson TK1.

Time and Sequence Integrated Runtime Anomaly Detection for Embedded Systems

Network-connected embedded systems are vulnerable to increasing malware. While anomaly-based malware detection is effective, existing approaches incur significant overheads and are susceptible to mimicry attacks. We present a formal security model that defines normal system behavior including execution sequence and timing. On-chip hardware non-intrusively monitors system execution and detect anomalies at runtime. The timing distribution of control flow events is further analyzed to select subset of monitoring targets to meet hardware constraints. The approach is evaluated using a network-connected pacemaker prototype and mimicry malware.

Improving Write Performance and Extending Endurance of Object-based NAND Flash Devices

In an object-based NAND flash device (ONFD), two causes of write amplification are onode partial update and cascading update. Updating one onode, a small-sized object metadata invokes partial page update (i.e., onode partial update), incurring unnecessary migration of the un-updated data. Cascading update denotes updating object metadata in a cascading manner due to object data update or migration. In this work, we propose a system design to alleviate the write amplification issue in the object-based NAND flash device. Experiment results show that our proposed design can achieve up to 20% write reduction compared to the best state-of-the-art.

Simulation-driven reachability using matrix measures

A key step in simulation-driven algorithms is to compute the reach set over-approximations from a set of initial states through numerical simulations and sensitivity analysis. This paper addresses this problem by providing algorithms for computing discrepancy functions as the upper bound on the sensitivity. The proposed algorithms rely on computing local bounds on matrix measures under different norms such that the over-approximations can be computed fast or its conservativeness is locally minimized. The proposed algorithms enable automatic reach set computations of general nonlinear systems and have been successfully used on several challenging benchmark model.

Efficient Schedulability Test for Dynamic-Priority Scheduling of Mixed-Criticality Real-Time Systems

In safety-critical systems, there are typically different applications providing functionalities with varying degrees of criticality. Consequently, high levels of assurance is required for a highly critical functionality, whereas relatively low levels of assurance is required for a less critical functionality. A theory of real-time scheduling for such multi-criticality systems has been under development in the recent past. In particular, an algorithm called Earliest Deadline First with Virtual Deadlines (EDF-VD) has shown a lot of promise for systems in terms of practical performance. In this paper we design a new schedulability test based on demand bound functions for EDF-VD.

Analysis and Design of Adders for Approximate Computing

In this paper, we propose four Approximate Full Adders (AFAs) with design objective that Cout remains independent of Cin with minimal error probability. We exploit the proposed AFAs to construct an N-bit approximate adder which hereinafter is referred to as ApproxADD. For improving Error Distance (ED) and Error Rate (ER) of ApproxADD, we exploit the concept of carry-lifetime and Error Detection and Correction (EDC) logic, respectively. We evaluate efficiency of the proposed approach by comparing it with existing approximate adders. We inspect effectiveness of the proposed approach in real-life applications by demonstrating image compression and decompression using the ApproxADD.

Efficient, Long-Term Logging of Rich Data Sensors using Transient Sensor Nodes

ÿTransiently powered systems avoid large energy storage by computation during availability of harvested energy. Using an efficient Energy Management Unit with Dynamic Energy Burst Scaling, energy can be accumulated in an optimally sized capacitance and used to supply energy bursts to the load at their optimal power point. The maximum burst size and use of a Non-Volatile Memory Hierarchy can have a significant impact on the work done per unit of energy. Experiments with a long-term autonomous image acquisition application show that the energy per image can be reduced by 77.8%, at the price of a 65% larger energy buffer.

LOCUS: Low-Power Customizable Many-Core Architecture for Wearables

Application requirements, such as real-time response, are pushing wearable devices to leverage more powerful processors inside the SoC (System-on-chip). However, existing wearable devices are not well suited for such challenging applications due to poor performance. We propose LOCUS  a low-power, customizable, many-core processor for next-generation wearable devices. LOCUS combines customizable processor cores with a customizable network on a message-passing architecture to deliver very competitive performance/watt  an average 3.1x compared to quad-core ARM processors used in the stateof-the-art wearable devices, and an average 1.52x performance/watt improvement over a conventional 16-core shared-memory many-core architecture.

Run-time Performance and Power Optimization of Parallel Disparity Estimation on Many-Core Platforms

This paper investigates the use of many-core systems to execute the disparity estimation algorithm, used in stereo vision applications, as these systems can provide flexibility between performance scaling and power consumption. We present a learning-based runtime management approach which achieves a required performance threshold whilst minimizing power consumption through dynamic control of frequency and core allocation. Experimental results are obtained from a 61-core Intel Xeon-Phi platform for the above investigation. The same performance can be achieved with an average reduction in power consumption of 27.8% and increased energy efficiency by 30.04% when compared to DVFS control alone without runtime management.

D-PUF: An Intrinsically Reconfigurable DRAM PUF for Device Authentication and Random Number Generation

In this paper, we propose D-PUF, an intrinsically reconfigurable DRAM PUF based on refresh pausing. A key feature of the proposed DRAM PUF is reconfigurability, i.e., by varying the refresh-pause interval, the challenge-response behavior of the PUF can be altered, making it robust against various attacks. The paper is broadly divided into two parts. In the first part, we demonstrate the use of D-PUF in performing device authentication through a secure, low-overhead methodology. In the second part, we show the generation of true random numbers using D-PUF. The design is implemented and validated using several off-the-shelf DDR3 DRAM modules.

Underminer: A Framework for Automatically Identifying Non-converging Behaviors in Black Box System Models

Evaluation of industrial embedded control system designs is a time-consuming and imperfect process. While an ideal process would apply a formal verification technique such as model checking, for industrial scale control systems, these techniques are often difficult to use to verify performance aspects such as convergence. For industrial designs, engineers rely on testing processes to identify unexpected behaviors. We propose a novel framework called Underminer to improve the testing process; this is an automated technique to identify non-converging behaviors in embedded control system designs. It supports various convergence-like notions, such as those based on Lyapunov analysis and temporal logic formulae.

Testing Programs with Contextual Unfoldings

In this paper we present a new algorithm that combines contextual unfoldings and dynamic symbolic execution to systematically test multithreaded programs. The approach uses symbolic execution to limit the number of input values and unfoldings to limit the number of thread interleavings that are needed to cover reachable local states of threads in the program under test. We show that the use of contextual unfoldings allows interleavings of threads to be succinctly represented. This can in some cases lead to a substantial reduction to the number of needed test executions when compared to previous approaches.

Guest Editorial for ACM TECS Special Issue on Autonomous Battery-Free Sensing and Communication

Harvest Energy from the Water: A Self-Sustained Wireless Water Quality Sensing System

A self-sustained water quality sensing system is designed where sensors are powered by renewable bio-energy generated from microbial fuel cells (MFC). MFC collect the energy released from native manganese oxidizing microorganisms (MOM) that are abundant in natural waters. A power management module and a radio-frequency (RF) activation technique are proposed to ensure precious energy harvested by MFC is used efficiently. The proposed system is implemented and evaluated in a stream. Results from three-month field experiments indicate that the proposed system is able to collect reliable water quality data and is robust to environment changes.

CaffePresso: Accelerating Convolutional Networks on Embedded SoCs

Auto-tuning and parametric implementation of deep learning kernels allow off-the-shelf accelerator-based embedded platforms to deliver high performance and energy efficient mappings for lightweight neural networks. Low-complexity classifiers are characterized by operations on small image maps with 23 deep layers and few class labels. For these use cases, we consider a range of embedded systems with 20 W power budget such as the Xilinx ZC706 (FPGA), NVIDIA Jetson TX1 (GPU), TI Keystone II (DSP) and the Adapteva Parallella (RISC+NoC). In Caffe- Presso, we combine auto-tuning of the implementation parameters, and platform-specific constraints deliver optimized solution for each input ConvNet specification.

DC4CD: a Platform for Distributed Computing on Constrained Devices

In this paper we present Distributed Computing for Constrained Devices (DC4CD), a novel software architecture that supports symbolic distributed computing on Wireless Sensor Networks. DC4CD integrates the functionalities of a high-level symbolic interpreter, a compiler, and an operating system, and includes networking abstractions to exchange high-level symbolic code among peer devices. Contrarily to other architectures proposed in literature, DC4CD allows for changes at runtime, even on deployed nodes of both application and system code. Experimental results show that DC4CD is more efficient in terms of memory usage than existing architectures, with which also compares well in terms of execution efficiency.

OPPC: An Optimal Path Planning Charging Scheme Based on Schedulability Evaluation for WRSNs

The lack of schedulability evaluation of previous charging schemes in wireless rechargeable sensor networks (WRSNs) degrades the charging efficiency, leading to energy exhaustion. We propose an optimal path planning charging scheme, namely OPPC, under the on-demand charging architecture. OPPC evaluates the schedulability of a charging mission, which makes charging scheduling predictable. OPPC provides an optimal charging path which enhances the charging performance. When confronting with a non-schedulable charging mission, a couple of mission adjusting algorithms are developed to enable the schedulability. Simulation results demonstrate that OPPC can achieve better performance in successful charging ratio as well as charging efficiency.

A Majority-Based Reliability-Aware Task-Mapping in High-Performance Homogenous NoC Architectures

This paper presents a new reliability-aware task mapping approach in a many-core platform at design time for applications with DAG-based task graphs. The main goal is to devise a task mapping which meets a predefined reliability threshold considering a minimized performance degradation. The proposed approach uses a majority-voting replication technique to fulfill error-masking capability. A quantitative reliability model is also proposed for the platform. Our iterative approach is applicable to an unlimited number of system fault types. All parts of the platform including cores, links and routers are assumed to be prone to failur

Exploiting approximate MLC-PCM in low-power embedded systems

The drift phenomenon can degrade the quality of result (QoR) of applications in presence of approximate MLC-PCM. The architecture-level techniques to alleviate the effects of the drift incur considerable power overhead in embedded systems (about 100%). In this paper, we utilize the DVFS technique to speed up the execution of the application when the profiling shows the drift-based errors are more probable to decrease the probability of drift-based soft errors. But, we speed up the application to save energy when the drift is not threating. Power overhead is improved by 84% (in average) in our approach, while QoR is acceptable.

Green-energy-powered Cognitive Radio Networks: Joint Time and Power Allocation

Security in embedded systems: Design challenges

Real-time garbage collection for flash-memory storage systems of real-time embedded systems

Dynamic allocation for scratch-pad memory using compile-time decisions

Power management in energy harvesting sensor networks

A log buffer-based flash translation layer using fully-associative sector translation

The worst-case execution-time problem—overview of methods and survey of tools

A reconfigurable FTL (flash translation layer) architecture for NAND flash-based applications

An optimal memory allocation scheme for scratch-pad-based embedded systems

Sensor deployment and target localization in distributed sensor networks

Energy management for battery-powered embedded systems

Bibliometrics

Publication Years 2002-2017
Publication Count 993
Citation Count 4693
Available for Download 992
Downloads (6 weeks) 3666
Downloads (12 Months) 36584
Downloads (cumulative) 452655
Average downloads per article 456
Average citations per article 5
First Name Last Name Award
Vikram Adve ACM Fellows (2014)
ACM Software System Award (2012)
Rajeev Alur ACM Fellows (2007)
Jose Nelson Amaral ACM Distinguished Member (2014)
ACM Senior Member (2012)
David F Bacon ACM Fellows (2009)
ACM Distinguished Member (2006)
Luca Benini ACM Fellows (2016)
Nirupama Bulusu ACM Senior Member (2014)
Krishnendu Chakrabarty ACM Fellows (2013)
ACM Distinguished Member (2008)
ACM Senior Member (2006)
Naehyuck Chang ACM Fellows (2015)
ACM Distinguished Member (2012)
ACM Senior Member (2007)
Alok Choudhary ACM Fellows (2009)
Jason Cong ACM Fellows (2008)
David Culler ACM Fellows (2002)
Ron Cytron ACM Fellows (2010)
Jack Davidson ACM Fellows (2008)
Giovanni DeMicheli ACM Fellows (2001)
Nikil D. Dutt ACM Fellows (2014)
ACM Distinguished Member (2007)
Deborah Estrin ACM Athena Lecturer Award (2006)
ACM Fellows (2000)
Ophir Frieder ACM Fellows (2005)
Kevin Fu ACM Senior Member (2010)
Soheil Ghiasi ACM Senior Member (2015)
Rachid Guerraoui ACM Fellows (2012)
Rajesh Gupta ACM Fellows (2016)
Rajiv Gupta ACM Fellows (2009)
John P Hayes ACM Fellows (2001)
John Heidemann ACM Senior Member (2007)
Maurice Herlihy ACM Fellows (2005)
Mary Jane Irwin ACM Athena Lecturer Award (2010)
ACM Distinguished Service Award (2005)
ACM Fellows (1996)
Niraj Jha ACM Fellows (2003)
Chandra Krintz ACM Senior Member (2009)
Tei-Wei Kuo ACM Fellows (2015)
Chris Lattner ACM Software System Award (2012)
John Lee ACM Senior Member (2014)
Yunhao Liu ACM Fellows (2015)
Yunhao Liu ACM Presidential Award (2013)
Nancy Lynch ACM Athena Lecturer Award (2012)
ACM Fellows (1997)
Roman Lysecky ACM Senior Member (2014)
Sharad Malik ACM Fellows (2014)
Diana Marculescu ACM Distinguished Member (2011)
ACM Senior Member (2009)
Margaret Martonosi ACM Fellows (2009)
Prabhat Mishra ACM Distinguished Member (2015)
ACM Senior Member (2010)
Trevor Mudge ACM Fellows (2016)
ACM-IEEE CS Eckert-Mauchly Award (2014)
Walid Najjar ACM Distinguished Member (2015)
ACM Senior Member (2014)
Vijaykrishnan Narayanan ACM Fellows (2014)
Peng Ning ACM Senior Member (2007)
Steven M Nowick ACM Senior Member (2009)
Martin Odersky ACM Fellows (2007)
Krishna Palem ACM Fellows (2005)
Massoud Pedram ACM Distinguished Member (2008)
Dhiraj Pradhan ACM Fellows (1999)
Viktor Prasanna ACM Fellows (2007)
Ragunathan Rajkumar ACM Distinguished Member (2007)
Binoy Ravindran ACM Distinguished Member (2014)
Martin Rinard ACM Fellows (2009)
Alberto Luigi Sangiovanni Vincentelli ACM Fellows (2014)
Lui Sha ACM Fellows (2005)
Yibing Shan ACM Gordon Bell Prize
Special Category (2009) ACM Gordon Bell Prize
Special Category (2009)
Kang Shin ACM Fellows (2001)
Sandeep K Shukla ACM Distinguished Member (2012)
ACM Senior Member (2007)
Daniel Siewiorek ACM Fellows (1994)
ACM-IEEE CS Eckert-Mauchly Award (1988)
Joseph Sifakis ACM Fellows (2012)
ACM A. M. Turing Award (2007)
Anand Sivasubramaniam ACM Distinguished Member (2010)
ACM Senior Member (2009)
John A Stankovic ACM Fellows (1996)
Per O Stenstrom ACM Fellows (2008)
Donald E Thomas ACM Fellows (2007)
Stamatis Vassiliadis ACM Fellows (2004)
Artemios G. Voyiatzis ACM Senior Member (2015)
David Whalley ACM Distinguished Member (2009)
ACM Senior Member (2009)
Reinhard Wilhelm ACM Distinguished Service Award (2010)
ACM Fellows (2000)
Mario Wolczko ACM Distinguished Member (2006)
Marilyn Claire Wolf ACM Fellows (2001)
Tilman Wolf ACM Senior Member (2007)
Tao Xie ACM Distinguished Member (2015)
ACM Senior Member (2011)
Zeljko Zilic ACM Senior Member (2009)

First Name Last Name Paper Counts
Nikil Dutt 18
Mahmut Kandemir 10
Luca Benini 9
Zebo Peng 8
Dimitrios Soudris 8
John Stankovic 8
Aviral Shrivastava 8
Francky Catthoor 8
Petru Eles 8
Niraj Jha 7
Shuvra Bhattacharyya 7
Rainer Leupers 7
Tian He 7
Lipin Chang 7
Mary Irwin 7
Prabhat Mishra 7
Majid Sarrafzadeh 6
Gerd Ascheid 6
Rajeev Barua 6
Tarek Abdelzaher 6
Frank Vahid 6
Anand Raghunathan 6
Frank Mueller 6
Yuanhao Chang 6
Narayanan Vijaykrishnan 6
Zili Shao 6
Roman Lysecky 6
Anand Paul 6
Chunjason Xue 6
Catherine Gebotys 6
Kostas Siozios 5
Luciano Lavagno 5
Teiwei Kuo 5
Ann Gordon-Ross 5
Insup Lee 5
Björn Franke 5
Mani Srivastava 5
Lothar Thiele 5
Alberto Sangiovanni-Vincentelli 5
Santosh Pande 4
Picheng Hsiu 4
Jinsoo Kim 4
Rolf Ernst 4
Chinhsien Wu 4
Peter Petrov 4
Srimat Chakradhar 4
Paul Caspi 4
Giorgio Buttazzo 4
Daniel Mossé 4
Meikang Qiu 4
Greg Stitt 4
Wayne Wolf 4
Guangyu Chen 4
David Whalley 4
Stavros Tripakis 4
Francisco Cazorla 4
Vijay Raghunathan 4
Dimitrios Serpanos 4
Yunsi Fei 4
Roozbeh Jafari 4
Chenyang Lu 4
Gang Qu 4
Jean Diguet 4
Eduardo Quiñones 4
Ingrid Verbauwhede 4
Bruce Jacob 4
Alex OrailoĞLu 4
Andy Wellings 4
Soheil Ghiasi 4
Davide Bertozzi 4
Lei Yang 3
Robert Dick 3
Gianluca Palermo 3
William Kaiser 3
Yuancheng Lai 3
Jingtong Hu 3
Ragunathan Rajkumar 3
Taejoon Park 3
Alain Girault 3
David Gregg 3
Victor Khomenko 3
Naehyuck Chang 3
Rance Rodrigues 3
Albert Benveniste 3
Seungryoul Maeng 3
Wei Zhang 3
Xenofon Koutsoukos 3
Qi Zhu 3
Zoran Salcic 3
Alan George 3
Yu Gu 3
Rajat Chakraborty 3
Keijo Heljanko 3
Miroslav Pajic 3
Nan Guan 3
Wang Yi 3
Benny Åkesson 3
Tim Güneysu 3
Alessandro Strano 3
Todor Stefanov 3
Martin Schoeberl 3
Yingdar Lin 3
Rajeev Alur 3
Marco Natale 3
Marco Caccamo 3
Bashir Al-Hashimi 3
Fadi Kurdahi 3
Massimo Poncino 3
Qingfeng Zhuge 3
Edward Lee 3
Najwa Aaraj 3
Sudeep Pasricha 3
Sarma Vrudhula 3
Paul Pop 3
Luca Carloni 3
Insik Shin 3
Jaejin Lee 3
Sanglyul Min 3
Peter Marwedel 3
Brian White 3
Gang Quan 3
Binoy Ravindran 3
Walid Najjar 3
Edwin Sha 3
Marc Geilen 3
Alan Burns 3
Jürgen Becker 3
Ahmed Jerraya 3
Xiaotong Zhuang 3
Ani Nahapetian 3
Kyoungwoo Lee 3
Kai Huang 3
Christopher Gill 3
Zhe Liu 3
Efstathios Sotiriou-Xanthopoulos 3
Yi Wang 3
Nathan Fisher 3
Yunheung Paek 3
Minyoung Kim 3
Donggang Liu 3
Giuseppe Lipari 3
Israel Koren 3
Rami Melhem 3
Tulika Mitra 3
E Jensen 3
Reinhard Wilhelm 3
Dakai Zhu 3
János Sztipanovits 3
Alexander Dean 3
Joseph Zambreno 3
Sotirios Xydis 3
George Economakos 3
Haibo Zeng 3
Krishnendu Chakrabarty 3
Jörg Henkel 3
Kuokun Tseng 3
Kang Shin 3
Jingling Xue 3
Chunjen Tsai 3
Avinash Malik 3
Bojan Mihajlović 2
Warren Gross 2
Timothy Bourke 2
Agustinus Waluyo 2
Alexandru Nicolau 2
William Mangione-Smith 2
Qi Dong 2
Martin Törngren 2
Mustafa Karaköy 2
Harini Ramaprasad 2
Foad Dabiri 2
Bhuvan Middha 2
Ke Bai 2
Yunhao Liu 2
Yafeng Wu 2
David Culler 2
Pedro Mejía-Alvarez 2
Seungmin Rho 2
Christos Ttofis 2
Ankush Varma 2
Igor Kozintsev 2
Paul Klein 2
Richard West 2
Dionisio De Niz 2
Jinjun Chen 2
Gang Chen 2
Jason Cong 2
Koen De Bosschere 2
Ludo Van Put 2
Stefan Petters 2
Kingshuk Karuri 2
Heinrich Meyr 2
Alberto Sangiovanni-Vincentelli 2
Paolo Ienne 2
Cristina Silvano 2
Samuel Rodrigo 2
Yooseong Kim 2
Stanley Bak 2
Elsayed Saad 2
Ahmed Eltawil 2
Karthik Shankar 2
Gabriela Nicolescu 2
Sean Whitty 2
Nadav Rotem 2
Junji Sakai 2
Xiao Qin 2
Wenny Rahayu 2
Vijaykrishnan Narayanan 2
Theocharis Theocharides 2
Jan Staschulat 2
Gabriel Parmer 2
Luigi Palopoli 2
Anupam Chattopadhyay 2
Sander Stuijk 2
Robert Davis 2
Andy Pimentel 2
Yohan Ko 2
Luis Murillo 2
Santanu Chattopadhyay 2
Jan Weinstock 2
Masud Ahmed 2
Kees Goossens 2
Alastair Murray 2
Mirko Loghi 2
Marco Paolieri 2
Joachim Falk 2
ZhiJun Ding 2
Mengchu Zhou 2
Matin Hashemi 2
Yineng Lin 2
Xiangrong Zhou 2
Alexander Veidenbaum 2
Amin Khajeh 2
Tiantian Liu 2
Minming Li 2
Weiche Tseng 2
Mike Gerdes 2
Florence Maraninchi 2
Daniel Siewiorek 2
Marco Bekooij 2
Flávio Wagner 2
Ismail Kadayif 2
Chantal Ykman-Couvreur 2
Artemios Voyiatzis 2
Iuliana Bacivarov 2
Rensong Tsay 2
Roozbeh Jafari 2
Daniel Grund 2
Sara Bocchio 2
Klaus Schneider 2
Chris Conger 2
Srivaths Ravi 2
Gang Zhou 2
Ting Yan 2
Roshan Ragel 2
Sri Parameswaran 2
Daqiang Zhang 2
Kartik Nagar 2
Sandip Kundu 2
Alois Knoll 2
Duo Liu 2
Mehdi Kargahi 2
Dominique Chanet 2
Chenye Wu 2
Lucas Wanner 2
Jorge Surís 2
Franjo Ivančić 2
Vincent Nélis 2
Bruce Childers 2
Thomas Pöppelmann 2
Karunanithi Bharanitharan 2
Yongxin Zhu 2
Yun Liang 2
Dannyziyi Chen 2
Guillem Bernat 2
Debdeep Mukhopadhyay 2
Urbi Chatterjee 2
Hwajeong Seo 2
Ferenc Bujtor 2
Jing Zeng 2
Wan Fokkink 2
Preeti Panda 2
Sotirios Ziavras 2
Biao Hu 2
Jack Sampson 2
Abhik Roychoudhury 2
Morteza Mohaqeqi 2
Christof Paar 2
Andrea Acquaviva 2
Davit Mirzoyan 2
Houman Homayoun 2
Avinash Lingamneni 2
Tommaso Cucinotta 2
Luca Abeni 2
Jingyuan Li 2
Abdoulaye Gamatié 2
Hrishikesh Jayakumar 2
Anfeng Liu 2
Hakan Aydín 2
Francisco Triviño 2
Mihai Lazarescu 2
Wei Dong 2
Alessandro Cilardo 2
Arash Reyhani-Masoleh 2
Mohammed Hasan 2
Bjorn De Sutter 2
Bruno De Bus 2
Xiaobosharon Hu 2
Sheayun Lee 2
Nalini Venkatasubramanian 2
David Kammler 2
Peter Athanas 2
Patrick Schaumont 2
Nirupama Bulusu 2
John Lach 2
Antoine Girard 2
Frank Sem-Jacobsen 2
Twan Basten 2
Jun Yang 2
Michael Hübner 2
Olfa Mosbahi 2
Hanifa Boucheneb 2
JoAnn Paul 2
Chungta King 2
Masato Edahiro 2
Abhijit Davare 2
Rajiv Gupta 2
Roberto Passerone 2
Y Srikant 2
Jason Hiser 2
Enrico Bini 2
Enric Musoll 2
Unmesh Bordoloi 2
Jhingfa Wang 2
Tor Skeie 2
Jean Béchennec 2
Filip Pizlo 2
Jan Vitek 2
Seonyeong Park 2
Philip Brisk 2
Angel Dominguez 2
Nikolaos Voros 2
Peng Ning 2
Sascha Uhrig 2
Sanjoy Baruah 2
Christian Haubelt 2
Mohamed Khalgui 2
Yosi Ben-Asher 2
Joonwon Lee 2
Sejin Kwon 2
Pierre Paulin 2
Jihong Kim 2
Curt Schurgers 2
Mingchang Yang 2
Chuanjun Zhang 2
Nader Bagherzadeh 2
JeonguK Kang 2
Diana Marculescu 2
Christos Strydis 2
Bernhard Rinner 2
Sebastian Fischmeister 2
Alberto Rosti 2
Yuan Xie 2
Soonhoi Ha 2
Laurence Yang 2
Mario Casu 2
Mehran Mozaffari-Kermani 2
Reza Azarderakhsh 2
Antti Siirtola 2
Long Cheng 2
Christine Rochange 2
Terrence Mak 2
Rosa Badía 2
Reiley Jeyapaul 2
Valeria Bertacco 2
Alexandros Bartzas 2
Luca Santinelli 2
Elias Manolakos 2
Tobias Oder 2
Anand Sivasubramaniam 2
Arun Kejariwal 2
Axel Jantsch 2
Shaoxiong Hua 2
Jean Gaudiot 2
Henning Sahlbach 2
Jörg Mische 2
Jürgen Teich 2
Norman Scaife 2
Kamel Barkaoui 2
Taesun Chung 2
Miodrag Potkonjak 2
Christos Sofronis 2
Diana Göhringer 2
Ioannis Sourdis 2
Jan Reineke 2
Eric Rotenberg 2
Guido Araújo 2
Hassan Ghasemzadeh 2
Brian Blum 2
Jie Hu 2
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