The Disclosure Power of Shared Objects

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The desire and ability to place AI-enabled applications on the edge has grown significantly in recent years. However, the compute-, area-, and power-constrained nature of edge devices are stressed by the needs of the AI-enabled applications, due to a gener ...

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 ...

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 ...

The landscape of computing is changing, thanks to the advent of modern networking equipment that allows machines to exchange information in as little as one microsecond. Such advancement has enabled microsecond-scale distributed computing, where entire dis ...

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

As the volume of produced data is exponentially increasing, companies tend to rely on distributed systems to meet the surging demand for storage capacity. With the business workflows becoming more and more complex, such systems often consist of or are acce ...

Classical synchronous consensus algorithms are leaderless: processes exchange their proposals, retain the maximum value and decide when they see the same choice across a couple of rounds. Indulgent consensus algorithms are more robust in that they only req ...

Reliable broadcast is a communication primitive guaranteeing, intuitively, that all processes in a distributed system deliver the same set of messages. The reason why this primitive is appealing is twofold: (i) we can implement it deterministically in a co ...

Consensus protocols for asynchronous networks are usually complex and inefficient, leading practical systems to rely on synchronous protocols. The invention proposes an approach to simplify asynchronous consensus by building it atop a novel threshold logic ...

Micro-architectural behavior of traditional disk-based online transaction processing (OLTP) systems has been investigated extensively over the past couple of decades. Results show that traditional OLTP systems mostly under-utilize the available micro-archi ...

In this thesis, we revisit classic problems in shared-memory distributed computing through the lenses of (1) emerging hardware technologies and (2) changing requirements. Our contributions consist, on the one hand, in providing a better understanding of th ...

In order to get a better understanding of the interaction of plasma microinstabilities and associated turbulence with specific modes, an antenna is implemented in the global gyrokinetic Particle-In-Cell (PIC) code ORB5. It consists in applying an external ...

Biomolecular computing is the field of engineering where computation, storage, communication, and coding are obtained by exploiting interactions between biomolecules, especially DNA, RNA, and enzymes. They are a promising solution in a long-term vision, br ...

Online services are becoming more and more ubiquitous and keep growing in scale. At the same time, they are required to be highly available, secure, energy-efficient, and to achieve high performance. To ensure these (and many other) properties, replication ...

Distributed file systems often exhibit high tail latencies, especially in large-scale datacenters and in the presence of competing (and possibly higher priority) workloads. This paper introduces techniques for managing tail latencies in these systems, whil ...

Simulations of electrical activity of networks of morphologically detailed neuron models allow for a better understanding of the brain. State-of-the-art simulations describe the dynamics of ionic currents and biochemical processes within branching topologi ...

Modern asynchronous runtime systems allow the re-thinking of large-scale scientific applications. With the example of a simulator of morphologically detailed neural networks, we show how detaching from the commonly used bulk-synchronous parallel (BSP) exec ...

Whole Genome Sequencing is a process in the field of bioinformatics that transforms biological samples of DNA into an electronic dataset of genetic bases. The process consists of two sequential components. First, the laboratory process of sequencing transf ...

Current online applications, such as search engines, social networks, or file sharing services, execute across a distributed network of machines. They provide non-stop services to their users despite failures in the underlying network. To achieve such a hi ...

As hardware evolves, so do the needs of applications. To increase the performance of an application, there exist two well-known approaches. These are scaling up an application, using a larger multi-core platform, or scaling out, by distributing work to mul ...

The Disclosure Power of Shared Objects

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Exploring High-Performance and Energy-Efficient Architectures for Edge AI-Enabled Applications

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

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

Reliable Microsecond-Scale Distributed Computing

HPCache: Memory-Efficient OLAP Through Proportional Caching

Clouseau: Blockchain-based Data Integrity for HDFS Clusters

Leaderless Consensus

Dynamic Byzantine Reliable Broadcast

Asynchronous distributed coordination and consensus with threshold logical clocks

Micro-architectural analysis of in-memory OLTP: Revisited

Distributed Computing with Modern Shared Memory

Using an antenna as a tool for studying microturbulence and zonal structures in tokamaks with a global gyrokinetic GPU-enabled particle-in-cell code

Biosensors for Bimolecular Computing: a Review and Future Perspectives

Scaling Byzantine Fault Tolerance

Managing Tail Latency in Datacenter-Scale File Systems Under Production Constraints

Asynchronous Branch-Paralle Simulation of Detailed Neuron Models

Fully-Asynchronous Cache-Efficient Simulation of Detailed Neural Networks

Scaling Out Bioinformatics in the Data Center

System Support for Efficient Replication in Distributed Systems

Scalable Synchronization in Shared-Memory Systems: Extrapolating, Adapting, Tuning