Building Efficient Query Engines using High-Level Languages

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Modern data-driven science often consists of iterative cycles of data discovery, acquisition, preparation, analysis, model building and validation leading to knowledge discovery as well as dissemination at scale. The unique challenges of building and simul ...

Memory devices have returned to the spotlight due to increasing interest in using in-memory computing architectures to make data-driven algorithms more energy-efficient. One of the main advantages of this architecture is the efficient performance of vector ...

The miniaturization of integrated circuits (ICs) and their higher performance and energy efficiency, combined with new machine learning algorithms and applications, have paved the way to intelligent, interconnected edge devices. In the medical domain, they ...

Modern computing systems are so energy- intensive to make efficient cooling vital for their operation. This is giving rise to a variety of innovative cooling solutions based on a mix of traditional and new techniques. The design and engineering of these so ...

This thesis demonstrates that it is feasible for systems code to expose a latency interface that describes its latency and related side effects for all inputs, just like the code's semantic interface describes its functionality and related side effects. S ...

Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...

Energy efficiency is crucial for the sustainable operation of all industrial and urban sectors. However, practicing engineers have seldom access to open-source tools that can readily evaluate and compare scenarios in terms of energy consumption, cost, and ...

By supporting the access of multiple memory words at the same time, Bit-line Computing (BC) architectures allow the parallel execution of bit-wise operations in-memory. At the array periphery, arithmetic operations are then derived with little additional o ...

The AIDRES database aims to support the long-term objective of a fully integrated industrial strategy in the EU 27, providing a service to the European Commission and a catalogue for industries to understand the effectiveness, efficiency and cost of potent ...

Embedded systems confront two opposite goals: low-power operation and high performance. The current trend to reach these goals is toward heterogeneous platforms, including multi-core architectures with heterogeneous cores and hardware accelerators. The lat ...

Structure determination of materials is key to understanding their physical properties. While single-crystal X-ray diffraction is the gold standard for structures displaying long-range order, many materials of interest are polycrystalline and/or disordered ...

Building Efficient Query Engines using High-Level Languages

Chattez avec Graph Search

Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science

How to Achieve Large-Area Ultra-Fast Operation of MoS 2 Monolayer Flash Memories?

Exploring brain-inspired multi-core heterogeneous hardware templates for low-power biomedical embedded systems

Object-oriented modelling of advanced computer cooling solutions

Latency Interfaces for Systems Code

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

ROSMOSE: A Web-based Optimization Tool to Aid Decision-making for the Design and Operation of Industrial and Urban Energy Systems

Bit-Line Computing for CNN Accelerators Co-Design in Edge AI Inference

AIDRES: A database for the decarbonisation of the heavy industry in Europe

Acceleration of Control Intensive Applications on Coarse-Grained Reconfigurable Arrays for Embedded Systems

NMR Crystallography in the Big Data Era: New Methods and Applications Powered by Machine Learning