Key Dates

Camera-Ready Papers Due

April 4, 2018
March 31, 2018

Early Registration Deadline

April 13, 2018
April 9, 2018
To register, click here.


Submit your paper here

Download CFP

TXT Format PDF Format


Gold Sponsors

Silver Sponsors

Previous Conferences

2017, 2016, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008, 2007, 2006, 2005, 2004

General Co-Chairs

David Kaeli
Northeastern University, US
Miquel Pericas
Chalmers University of Technology, SE

Program Co-Chairs

Miquel Moreto
Barcelona Supercomputing Center, ES
Josef Weidendorfer
Leibniz Supercomputing Centre /
Technical University of Munich, DE

For more information, visit the website at


Computing Frontiers 2018 will feature four co-located workshops. Submission of papers to the workshops is handled separately from the main conference. Please refer to the websites of the workshops for submission deadlines and more details.

International Workshop on Big Data Analytics (BigDAW '18)

Aim and Scope:
Managing and processing large volumes of data, or "Big Data", and gaining meaningful insights is a significant challenge facing the distributed computing community. As a consequence, many business are demanding large-scale streaming data analytics. This has a significant impact on a wide range of domains, including health care, bio-medical research, Internet searches, finance and business informatics, and scientific computing.

Despite considerable progress in high performance, storage capacity, and computation power, challenges remain in identifying, clustering, classifying, and interpreting a large spectrum of information.

The purpose of this workshop is to provide a fertile ground for collaboration among research institutions and industries in the fields of analytics, machine learning, and high-performance computing.

Topics of interest:

  • High-performance data analytics
  • Machine and deep learning
  • Data search and representation
  • Architecture and system design
  • Cloud-based Big Data solutions
  • Software infrastructures

Workshop Website:

4th Workshop on Design of Low Power EMbedded Systems (LP-EMS '18)

Aim and Scope:
Modern cyber-physical and highly networked systems impose to designers challenging and conflicting requirements. Implementing real-time high-performance systems and minimizing, contemporarily, their power consumption is not straightforward. Emergent and unpredictable behaviours require these systems to adapt at runtime to mutable conditions. Therefore, advanced modelling strategies as well as efficient design automation techniques should be capable of optimizing complex parallel applications over heterogeneous multi- and many-cores platforms. Complexity on algorithmic side and heterogeneity on hardware side are colliding system constraints, which can be tackled by adopting hw/sw co-design solutions and flexible design frameworks.

With respect to this context, contributions are expected in different fields of digital signal processing such as: telecommunication, multimedia, medical imaging, computing graphics, biomedical applications and many others!

Papers may include, but are not limited to, the following topics:

  • High-level synthesis and HW/SW co-design techniques for low-power digital signal/image processing;
  • Design of self-energy aware systems;
  • Design space exploration techniques, with special emphasis on power/energy estimations and power minimization methodologies;
  • Parallel/high throughput processing techniques for low-power digital signal/image processing;
  • Algorithm-level optimization, low-complexity algorithm for low-power digital signal/image processing;
  • MPEG Green Metadata;
  • Approximate computing, low power arithmetic
  • Dynamic voltage and frequency scaling, HW and SW dynamic power management.

Workshop Website:

Malicious Software and Hardware in Internet of Things (MaL-IoT '18)

Aim and Scope:
Cyber-physical and smart embedded systems, already highly networked, will be even more connected in the near future to form the Internet of Things, handling large amount of private and safety critical data. The pervasive diffusion of these devices will create several threats to privacy and could open new possibilities for attackers, since the security of even large portions of the Internet of Things could be harmed by compromising a reduced number of components. The possibility of securely updating devices should be guaranteed and it should be possible to verify and assert the root of trust of components. With respect to this context we expect contributions in different areas of security in Internet of Things. Topics of the workshop include but are not limited to:

  • Malicious firmware design and detection
  • Malware in Internet of Things applications
  • Hardware root of trust
  • Privacy issues of smart-home systems and complex systems
  • Hardware Trojans and their effects on systems
  • Hardware authentication and IP protection
  • Secure communication and key-management
  • Implementation attacks and countermeasures
  • Emerging threats and attack vectors in the Internet of Things
  • Supply chain security

Workshop Website:

Workshop on Sensor Data Fusion and Machine Learning for the Next Generation of Cyber-Physical Systems (SeFuMAL '18)

Aim and Scope:
This Workshop provides latest achievements in sensor and information data fusion (IFU) and machine learning (ML) for cyber-physical-systems. The automotive industry, the process industry, robotics and many others adopted methodologies from IFU and ML which have never been used before. The workshop opens the floor for discussions with academic and industrial representatives who are involved in this next generation of system and application design. The Workshop targets presentations within the following fields of Research:

  • Algorithms and methods for sensor data fusion and / or machine learning
  • Machine Learning / Sensor data fusion for IoT
  • Machine Learning / Sensor data fusion for Cyberphysical Systems
  • Reconfigurable Hardware deployment for Sensor data fusion and / or Machine Learning
  • Novel Hardware architectures for machine Learning and sensor data fusion
  • Industrial applications using sensor data fusion and machine learning

Workshop Website: