TOUCH: In-Memory Spatial Join by Hierarchical Data-Oriented Partitioning

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Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

Computer systems rely heavily on abstraction to manage the exponential growth of complexity across hardware and software. Due to practical considerations of compatibility between components of these complex systems across generations, developers have favou ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

The manuscript describes the development of a spatial Agent-based Simulation to model the effect of public policies on private houseowner’s decisions concerning their heating system. The methodology utilized comprises of an empirical survey to determine th ...

In the past decades, a significant increase of the transistor density on a chip has led to exponential growth in computational power driven by Moore's law. To overcome the bottleneck of traditional von-Neumann architecture in computational efficiency, effo ...

We focus on distinctive data-driven measures of the fate of ongoing epidemics. The relevance of our pursuit is suggested by recent results proving that the short-term temporal evolution of infection spread is described by an epidemicity index related to th ...

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 ...

Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today'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 ...

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

Analytical engines rely on in-memory data caching to avoid storage accesses and provide timely responses by keeping the most frequently accessed data in memory. Purely frequency- and time-based caching decisions, however, are a proxy of the expected query ...

Information derived from experiences is incorporated into the brain as changes to ensembles of cells, termed engram cells, which allow memory storage and recall. The mechanism by which those changes hold specific information is unclear. Here, we test the h ...

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 ...

Modern hardware is increasingly complex, requiring increasing effort to understand in order to carefully engineer systems for optimal performance and effective utilization. Moreover, established design principles and assumptions are not portable to modern ...

ML-based edge devices may face memory and computational errors that affect applications' reliability and performance. These errors can be the result of particular working conditions (e.g., radiation areas in physical experiments or avionics) or could be th ...

To build biophysically detailed models of brain cells, circuits, and regions, a data-driven approach is increasingly being adopted. This helps to obtain a simulated activity that reproduces the experimentally recorded neural dynamics as faithfully as possi ...

The generation of 3D models depicting cities in the past holds great potential for documentation and educational purposes. However, it is often hindered by incomplete historical data and the specialized expertise required. To address these challenges, we p ...

Compute memories are memory arrays augmented with dedicated logic to support arithmetic. They support the efficient execution of data-centric computing patterns, such as those characterizing Artificial Intelligence (AI) algorithms. These architectures can ...

Most modern in-memory online transaction processing (OLTP) engines rely on multi-version concurrency control (MVCC) to provide data consistency guarantees in the presence of conflicting data accesses. MVCC improves concurrency by generating a new version o ...

Traumatic events generate some of the most enduring memories, yet little is known about how long-lasting fear memories can be attenuated. In this review, we collect the surprisingly sparse evidence on remote fear memory attenuation from both animal and hum ...

TOUCH: In-Memory Spatial Join by Hierarchical Data-Oriented Partitioning

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EdgeAI-Aware Design of In-Memory Computing Architectures

Secure Interface Design Leveraging Hardware/Software Support

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Spatial Agent-Based Modelling and Simulation to Evaluate on Public Policies for Energy Transition

Towards Scalable Electronics: Synthetic 2D Materials for Large-Area 2D Circuit Integration

Epidemicity indices and reproduction numbers from infectious disease data in connected human populations

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

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

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

Rebooting Virtual Memory with Midgard

HPCache: memory-efficient OLAP through proportional caching revisited

Engram cell connectivity as a mechanism for information encoding and memory function

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

Chaosity: Understanding Contemporary NUMA-architectures

Hardware-Software co-design Methodologies for Edge AI Optimization

Online interoperable resources for building hippocampal neuron models via the Hippocampus Hub

Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

Overflow-free compute memories for edge AI acceleration

One-shot Garbage Collection for In-memory OLTP through Temporality-aware Version Storage

Face your fears: attenuating remote fear memories by reconsolidation-updating