Modern High Level Synthesis (HLS) tools succeed well in their engineering productivity goal, but still require toolset and target technology specific modifications to the source code to guide the process towards an efficient implementation. Furthermore, their end result is a fixed function accelerator with limited field and runtime flexibility. In this paper we describe the status of AEx, a novel work-in-progress HLS tool developed in the FitOptiVis ECSEL JU project. AEx is based on automated exploration of architectures using a flexible and lightweight parallel co-processor template. We compare its current performance in CHStone C-language benchmarks to the state of the art FPGA HLS tool Vitis, provide ASIC implementation numbers, and identify the main remaining toolset features that are expected to dramatically further improve the performance. The potential is explored with a hand-optimized case study that shows only 1.64x performance slowdown with the programmable co-processor in comparison to the fixed function Vitis HLS result.@en

Cyber-Physical Systems (CPS) are systems that are in feedback with their environment, possibly with humans in the loop. They are often distributed with sensors and actuators, smart, adaptive and predictive and react in real-time. Image- A nd video-processing pipelines are a prime source for environmental information improving the possibilities of active, relevant feedback. In such a context, FitOptiVis aims to provide end-to-end multi-objective optimization for imaging and video pipelines of CPS, with emphasis on energy and performance, leveraging on a reference architecture, supported by low-power, high-performance, smart devices, and by methods and tools for combined design-time and run-time multi-objective optimization within system and environment constraints.@en

Cyber-Physical Systems (CPS) are systems that are in feedback with their environment, possibly with humans in the loop. They are often distributed with sensors and actuators, smart, adaptive and predictive and react in real-time. Image- A nd video-processing pipelines are a prime source for environmental information improving the possibilities of active, relevant feedback. In such a context, FitOptiVis aims to provide end-to-end multi-objective optimization for imaging and video pipelines of CPS, with emphasis on energy and performance, leveraging on a reference architecture, supported by low-power, high-performance, smart devices, and by methods and tools for combined design-time and run-time multi-objective optimization within system and environment constraints.@en

Many applications make extensive use of various forms of compression techniques for storing and communicating data. As decompression is highly regular and repetitive, it is a suitable candidate for acceleration. Examples are offloading (de)compression to a dedicated circuit on a heterogeneous System-on-Chip, or attaching FPGAs or ASICs directly to storage so they can perform these tasks on-the-fly and transparently to the application. ASIC or FPGA implementations will usually result in higher energy-efficiency compared to CPUs. Various ASIC and FPGA accelerators have been developed, but they typically target a single algorithm. However, supporting different compression algorithms could be desirable in many situations. For example, the Apache Parquet file format popular in Big Data analytics supports using different compression standards, even between blocks in a single file. This calls for a more flexible software based co-processor approach. To this end, we propose a compiler-supported Application-Specific Instruction-set Processor (ASIP) design that is able to decompress a range of lossless compression standard without FPGA reconfiguration. We perform a case study of searching a compressed database dump of the entire English Wikipedia. @en

ALMARVI is a collaborative European research project funded by Artemis involving 16 industrial as well as academic partners across 4 countries, working together to address various computational challenges in image and video processing in 3 application domains: healthcare, surveillance and mobile. This paper is an editorial for a special issue discussing the integrated system created by the partners to serve as a cross-domain solution for the project. The paper also introduces the partner articles published in this special issue to discuss the various technological developments achieved within ALMARVI spanning all system layers, from hardware to applications. We illustrate the challenges faced within the project based on use cases from the three targeted application domains, and how these can address the 4 main project objectives addressing 4 challenges faced by high performance image and video processing systems: massive data rate, low power consumption, composability and robustness. We present a system stack composed of algorithms, design frameworks and platforms as a solution to these challenges. Finally, the use cases from the three different application domains are mapped on the system stack solution and are evaluated based on their performance for each of the 4 ALMARVI objectives.@en