Reconfigurable computing has been gaining attention in both the high-performance computing (HPC) and the high-performance embedded computing (HPEC) communities. The synergistic use of multiprocessing techniques and reconfigurable parallelism has shown orders of magnitude improvements in performance, power efficiency, and cost for many applications. Numerous emerging architectures (homogeneous/heterogeneous Multi-processor Systems-on-Chips, embedded FPGAs, self-organizing computing substrates), techniques (dynamic/partial reconfiguration, run-time adaptability, hardware virtualization) and paradigms shifts (anti-machines, evolvable/bio-inspired systems) open new perspectives and contribute to widen the spectrum of potential benefits of reconfigurable hardware. However, widespread adoption of this technology is hampered by numerous difficulties in using the hardware and software. Both architectures and programming tools/methodologies lack the proper maturity and therefore pose severe limitations in term of usability for high-performance computing applications and high-performance embedded systems.

The High-Performance Reconfigurable Computing (HPRC) track at ReConFig invites submissions from researchers and developers from this field as well as application scientists and HPC/HPEC communities attempting to use this technology to implement computationally intensive applications.

Topics
• Systems and emerging architectures
• Dynamic Hardware reconfiguration
• Reconfigurable instruction set/VLIW processors and MPSoC architectures
• High-level Languages, compilers, and tools
• Run-time environments
• Libraries, standards, and interoperability
• Performance modeling, prediction, and benchmarks
• Software-hardware co-design methodology, algorithms, and formal methods
• Scientific and engineering applications
• Novel FPGA architectures for HPRC including 3D FPGAs
• FPGAs using emerging technologies

Inspiration from the principles driving the emergent properties observed in living beings has been successfully applied for centuries in order to tackle complex engineering problems. However, the recent advances in semiconductor technology and especially the availability of reconfigurable platforms with outstanding performance and capacity figures have paved the way for a broad use of bioinspired techniques in everyday general purpose applications. As a consequence, electronic systems endowed with learning, development, self-repair, self-replication or evolution capabilities are currently used for addressing sensing, information processing and control in domains as diverse as aeronautics and aerospace, security or telecommunications. On the other hand, the advent of deep submicron silicon fabrication technologies has made available multi-billion transistor devices for which the design efforts have to cope not only with their inherent complexity, but also with eventual deviations from their normal operating conditions due to defects, technological variability or influence of the power consumption in the device parameters. Even if these issues could be addressed externally, the inherent complexity of these devices demands for autonomous, in-system and distributed self-adaptive mechanisms, like dynamic temperature management or dynamic frequency and voltage scaling. Since biological organisms are also made up of individual subsystems that are inherently self-adaptive, it is envisioned that bioinspired computing principles will play a major role in the development and deployment of actual self-adaptive systems.

Papers that are related to both reconfigurable computing and bioinspiration or self-adaptation are welcome. We seek contributions in the area of bioinspired or self-adaptive approaches applied to reconfigurable systems and devices, as well as contributions about reconfigurable implementations of bioinspired and self-adaptive systems. Topics include, but are not limited to:

• Bioinspired models and architectures for reconfigurable computing
• Evolvable hardware
• Design methodologies and tools for bioinspired reconfigurable systems
• Fault-tolerant and self-repair systems
• Self-organizing reconfigurable computing systems
• Bioinspired multi-agent models on reconfigurable hardware
• Reconfigurable implementations of learning mechanisms and artificial neural networks
• On-line monitoring and diagnostic methods
• Self-adaptive run-time reconfiguration
• Models and architectures for self-adaptive systems
• Temperature and power aware computing systems
• Variability aware computing systems
• Verification and validation for evolvable, self-repair/self-adaptive systems
• Practical applications of reconfigurable bioinspired and self-adaptive systems

Reconfigurable hardware offers unique opportunities for the design and implementation of secure applications in embedded and high-end computing platforms. High performance, carefully-controlled execution, and physical isolation are just a few of the advantages that hardware brings over software. At the same time, new challenges appear, such as the protection of intellectual property in a reconfigurable fabric, and the protection of soft-hardware against malicious tampering. This special track seeks the latest innovations in reconfigurable computing for security and cryptography. Topics of interest include the following:

• Hardware Implementation of Novel Cryptographic Algorithms and Protocols
• Reconfigurable Cryptographic Primitives
• Special-Purpose Hardware for Cryptanalysis
• Hardware Support for Trustworthy Software Execution
• True and Pseudo Random Generators
• Circuit Identification and Physical Unclonable Functions
• Efficient Methods for Protection of Hardware IPs
• FPGA Design Security
• Fault Attacks and Side-channel Attacks
• Hardware Tamper Resistance and Tamper Evidence
• Hardware Trojan Detection and Resistance
• Design Flows for Hardware-based Secure Systems
• Performance Evaluation of Secure Reconfigurable Hardware

The inherent parallelism in DSP algorithms and communication applications lends itself ideally to hardware implementation. Reconfigurable platforms have garnered wide use in the field, with communications companies still the primary users of programmable logic devices. With rapidly evolving standards and the constraints on time-to market, reconfigurable systems can provide an important edge in a fierce market. Manufacturers of programmable logic devices have recognised this, and continued to provide architectural features tailored to this field of application, thus enabling novel mappings of complex algorithms and systems.

Recent developments in the communications field include a move to more adaptive systems. Cognitive radios are intelligent systems that adapt to environmental and infrastructure conditions in order to provide the best possible service and use of resources. Such systems are typically computationally intensive, and require significant reconfigurability, making them ideal candidates for implementation on reconfigurable platforms.

Authors are invited to submit original contributions related to the following topics:
• Platforms and tools for adaptive and cognitive radio systems
• Novel reconfigurable architectures for communications and DSP Applications
• Coarse-grain architectures for DSP
• Low-power DSP architecture and implementation
• Design tools for DSP and communications on reconfigurable platforms
• Novel algorithms for DSP on reconfigurable platforms
• Exploiting heterogenous resources on modern programmable logic devices for DSP application

High-performance computing systems, for high-end servers as well or for embedded systems, a massive paradigm shift towards multicore architectures is taking place. Integrating multiple cores on a single chip leads to a significant performance improvement without increasing the clock frequency. Multicore architectures offer a better performance/Watt ratio than single core architectures with similar performance. Combining multicore and coprocessor technology promise extreme computing power for highly CPU-time-consuming applications in scientific computing as well as for special purpose applications in the embedded area. Especially FPGA-based accelerators not only offer the opportunity to speedup an application by implementing their compute-intensive kernels into hardware but also to adapt to the dynamical behavior of an application. The purpose of this workshop is to evaluate strategies for future system design in MPSoC architectures. Both aspects, hardware design and tool-integration into existing development tools will be discussed. Especially the novel trends in MPSoC combined with reconfigurable architectures are a main topic in this workshop. Furthermore, the on-chip intercommunication affects tremendously the performance of the complete device and is therefore a topic of high importance in this track.

Authors are invited to submit original contributions related to the following topics:

• Overview of actual and future Multiprocessor System on Chip (current architectures from industry and academics, future trends)
• Tool Adaption / Extension for handling the complexity of actual and novel architectures
• Reconfiguration Methods: Solution for well balanced load distribution on chip?
• Industrial interests: Fields of application for MPSoC architectures
• Multilevel parallelization and hybrid concepts on hierarchical systems
• New optimized algorithms adapted to the specific architectures
• Numerical methods compliant with the memory hierarchy
• Adaptive schemes on heterogeneous architectures
• Providing powerful programming models allowing programmers to express parallelism, data access, and synchronization
• Supporting code partitioning between hardware and software
• Developing tools for performance analysis and debugging
• Virtualization technology to abstract applications from the underlying multicore architecture

FPGAs (Field-Programmable Gate Arrays) are used to accelerate a wide spectrum of applications, in embedded as well as high-performance systems. Most current uses of FPGAs are static, where a design is programmed once and then used to execute the application. Partial and dynamic reconfiguration allow the reuse of hardware resources and possible hardware cost savings. Furthermore, by adopting dynamic reconfiguration, a system is able to accomplish virtualization, which can be used to allow portability.
This track aims at providing a forum to discuss and present state-of-the-art industrial and academic experiences concerning reconfiguration techniques. Papers with contributions to the following topics are particularly welcome:

• The use of reconfiguration techniques to improve performance, save area, energy, etc.
• Reconfiguration techniques to customize hardware resources (interconnections, functional units, buffers, multicore interconnect topologies, etc.)
• Dynamic adaptation of architectures
• Runtime mapping techniques allowed by dynamic reconfiguration
• Hardware virtualization
• Programming models and languages supporting reconfiguration techniques
• Operating Systems supporting reconfiguration techniques
• Design and compilation flows for dynamically reconfigurable devices
• The use of dynamic reconfiguration techniques for prototyping circuits and systems
• Reconfiguration techniques to deal with unreliability and to improve fault tolerance
• Applications taking advantage of reconfiguration techniques

FPGAs has gained interest on robotics and mobile robotics applications due to their flexibility to implement from glue logic, up to complete embedded systems for robot control and high level processing. The synergy between robotics and reconfigurable computing is opening new research and application opportunities to build better and more intelligent robots. The special Reconfig track on FPGAs for robotics is aimed to research related to any aspect of Robotics where FPGA and Reconfigurable logic can have an impact. Topics include, but are not limited to:

• Reconfigurable Computing and FPGas in Mobile Robotics
• FPGA based platforms for robotics
• Robot navigation architectures
• Robot map creation architectures
• Robot protocol and communications
• Bioinspired sensing and controlling architectures implemented on FPGA
• Modular robotics
• Robotic control
• Vision processors based on FPGA