Abstract Web search is a crucial technology for the digital economy. Dominated by a few gatekeepers focused on commercial success, however, web publishers have to optimize their content for these gatekeepers, resulting in a closed ecosystem of search engines as well as the risk of publishers sacrificing quality. To encourage an open search ecosystem and offer users genuine choice among alternative search engines, we propose the development of an Open Web Index (OWI). We outline six core principles for developing and maintaining an open index, based on open data principles, legal compliance, and collaborative technology development. The combination of an open index with what we call declarative search engines will facilitate the development of vertical search engines and innovative web data products (including, e.g., large language models), enabling a fair and open information space. This framework underpins the EU‐funded project OpenWebSearch.EU, marking the first step towards realizing an Open Web Index.

Developing and optimizing software applications for high performance and energy efficiency is a very challenging task, even when considering a single target machine. For instance, optimizing for multicore-based computing systems requires in-depth knowledge about programming languages, application programming interfaces (APIs), compilers, performance tuning tools, and computer architecture and organization. Many of the tasks of performance engineering methodologies require manual efforts and the use of different tools not always part of an integrated toolchain. This paper presents Pegasus, a performance engineering approach supported by a framework that consists of a source-to-source compiler, controlled and guided by strategies programmed in a Domain-Specific Language, and an autotuner. Pegasus is a holistic and versatile approach spanning various decision layers composing the software stack, and exploiting the system capabilities and workloads effectively through the use of runtime autotuning. The Pegasus approach helps developers by automating tasks regarding the efficient implementation of software applications in multicore computing systems. These tasks focus on application analysis, profiling, code transformations, and the integration of runtime autotuning. Pegasus allows developers to program their strategies or to automatically apply existing strategies to software applications in order to ensure the compliance of non-functional requirements, such as performance and energy efficiency. We show how to apply Pegasus and demonstrate its applicability and effectiveness in a complex case study, which includes tasks from a smart navigation system.

The ANTAREX project developed an approach to the performance tuning of High Performance applications based on an Aspect-oriented Domain Specific Language (DSL), with the goal to simplify the enforcement of extra-functional properties in large scale applications. The project aims at demonstrating its tools and techniques on two relevant use cases, one in the domain of computational drug discovery, the other in the domain of online vehicle navigation. In this paper, we present an overview of the project and of its main achievements, as well as of the large scale experiments that have been planned to validate the approach.

Designing and optimizing applications for energy-efficient High Performance Computing systems up to the Exascale era is an extremely challenging problem. This paper presents the toolbox developed in the ANTAREX European project for autotuning and adaptivity in energy efficient HPC systems. In particular, the modules of the ANTAREX toolbox are described as well as some preliminary results of the application to two target use cases. 1

The ANTAREX project relies on a Domain Specific Language (DSL) based on Aspect Oriented Programming (AOP) concepts to allow applications to enforce extra functional properties such as energy-efficiency and performance and to optimize Quality of Service (QoS) in an adaptive way. The DSL approach allows the definition of energy-efficiency, performance, and adaptivity strategies as well as their enforcement at runtime through application autotuning and resource and power management. In this paper, we present an overview of the ANTAREX DSL and some of its capabilities through a number of examples, including how the DSL is applied in the context of one of the project use cases.

Continuously increasing application demands on both High Performance Computing (HPC) and Embedded Systems (ES) are driving the IC manufacturing industry on an everlasting scaling of devices in silicon. Nevertheless, integration and miniaturization of transistors comes with an important and non-negligible trade-off: time-zero and time-dependent performance variability. Increasing guard-bands to battle variability is not scalable, since worst-case design margins are prohibitive for downscaled technology nodes. This paper discusses the FP7-612069-HARPA project of the European Commission which aims to enable next-generation embedded and high-performance heterogeneous many-cores to cost-effectively confront variations by providing Dependable-Performance: correct functionality and timing guarantees throughout the expected lifetime of a platform under thermal, power, and energy constraints. The HARPA novelty is in seeking synergies in techniques that have been considered virtually exclusively in the ES or HPC domains (worst-case guaranteed partly proactive techniques in embedded, and dynamic best-effort reactive techniques in high-performance).

In this paper, we propose a safety-critical system with a run-time resource management that is used to operate an application for flood monitoring and prediction. This application can run with different Quality of Service (QoS) levels depending on the current hydrometeorological situation. The system operation can follow two main scenarios - standard or emergency operation. The standard operation is active when no disaster occurs, but the system still executes short-term prediction simulations and monitors the state of the river discharge and precipitation intensity. Emergency operation is active when some emergency situation is detected or predicted by the simulations. The resource allocation can either be used for decreasing power consumption and minimizing needed resources in standard operation, or for increasing the precision and decreasing response times in emergency operation. This paper shows that it is possible to describe different optimal points at design time and use them to adapt to the current quality of service requirements during run-time.