Algorithms, Design Methods, and Many-core Execution Platform for Low-Power Massive Data-Rate Video and Image Processing
Artemis 2013 GA 621439
The project provides the core of solutions for the big societal challenges like affordable healthcare and wellbeing, green and safe transportation, and reduced consumption of power.
1. Enable cross-domain re-use and interoperability for different product categories and application domains, thus promoting cross-fertilization and reuse of technology results.
2. Facilitate predictable system and product properties, and robust solutions.
3. Develop joint hardware-software techniques for resource and power management, yet providing massive data-rate processing and supporting interoperability over cross-domain platforms.
Advanced image and video processing systems are becoming a crucial and resource consuming part of embedded applications in many sectors. ALMARVI aims to facilitate the transition from a vertically structured market to a horizontally structured market. In particular, it focuses on reducing overall system design cost and time-to-market and enabling low cost solutions for high volume markets in different industrial domains and creating new market opportunities, and supporting SMEs.
The demonstrators developed under this project for the healthcare, security/surveillance/monitoring, and mobile use cases will directly lead to marketable applications and products in their relevant domains. Integrated releases of the image/video processing algorithm libraries, reference design tools and platforms, and system software stack solutions will be made available along with their evaluation for the demonstrated use cases. Cross-domain applicability will reduce fragmentation, thus increasing the market share of European supplier industry.
1. Reduce the cost of the system design 20% - 30% through modularity, flexible interfacing, adaptive architecture, execution platform with well-developed tool chains, adaptability and run-time configurability.
2. Reduce in development cycles 25% - up to 35% through seamless scalability and integration of hardware and software components and cross-domain component reuse, cross-domain system software stack, design tools, understanding of relevant system layers
3. Manage a complexity increase with 30% -60% effort reduction through novel algorithms, architecture, design tools, execution platforms, and system software stack with run-time adaptive resource and power management techniques
4. Reduce effort and time for re-validation and re-certification 15% - 20% through incremental design, develop, test, integrate, validate cycles.
5. Cross-sectoral re-usability of Embedded Systems 20% - 50% through system architecture accounting for the common requirements of different sectors and application domains.
The key is to leverage the properties of image/video content while jointly adapting algorithms and hardware in order to achieve a much higher potential for power savings and to enable massive data rate processing. At the Application Layer, the goal is to adapt algorithms towards the architectures. At the System Software Stack Layer, the adaptive run-time system allocates resources to different applications executing simultaneously in an energy-efficient way. At the Hardware Layer, the ALMARVI’s many-core execution platform provides the compute capabilities to diverse image/video processing applications.
IDEA 2016 workshop @ CPSWeek, April 2016
A keynote from Zaid Al-Ars, of TU Delft, NL on the multi-core architecture
High Performance Embedded Computing Using Heterogeneous Computational Fabrics — The ALMARVI Vision and Beyond
In the past decade, demand for high performance computing has been steadily increasing throughout the computing spectrum, all the way from high-end supercomputers, down to small handheld devices. To facilitate this need in the field of embedded computing, various concepts have been proposed to bring high performance architectures to the embedded domain. However, the diverse and in many cases stringent application requirements in this domain (such as low power, portability, form-factor limitations, etc.) have made it difficult to come up with a single design paradigm that satisfies the wide variation of available applications. This results in the need to develop custom-made solutions for each application, with an associated high cost of design, debug and verification of the hardware and application software. In this talk, we discuss the current trends in high performance embedded systems, where heterogeneous computing plays an important role in satisfying the computational requirements of the system on the one hand, while software abstraction ensures easy programmability and portability of the developed application software. We also present the ALMARVI project vision and ongoing activities as an example of this trend. Finally, we show how this trend into heterogeneous computing is also penetrating the high performance computing field, resulting in the convergence of various aspects of the computational spectrum from the high-end to the embedded world.
Dr. Dip Goswami
Amir R. B. Behrouzian