相关论文: The PROOF Distributed Parallel Analysis Framework …

The aim of this paper is to develop an approach to visualizations that benefits from distributed computing. Three schemes of process distribution are considered: parallel, pipeline, and expanding pipeline computations. Expanding pipeline…

This work introduces a compact framework for analyzing asynchronous entanglement distribution protocols under realistic error models. We focus on two contemporary protocols: sequential, where entanglement is established one node at a time,…

Concurrent data structures are the data sharing side of parallel programming. Data structures give the means to the program to store data, but also provide operations to the program to access and manipulate these data. These operations are…

New ideas in distributed systems (algorithms or protocols) are commonly tested by simulation, because experimenting with a prototype deployed on a realistic platform is cumbersome. However, a prototype not only measures performance but also…

We show how phase and amplitude estimation algorithms can be parallelized. This can reduce the gate depth of the quantum circuits to that of a single Grover operator with a small overhead. Further, we show that for quantum amplitude…

Testbed sharing, a practice in which different researchers concurrently develop independent use cases on top of the same testbed, is ubiquitous in wireless experimental research. Its key drawback is experimental inconvenience: one must…

In this era of large-scale data, distributed systems built on top of clusters of commodity hardware provide cheap and reliable storage and scalable processing of massive data. Here, we review recent work on developing and implementing…

In an emerging computing paradigm, computational capabilities, from processing power to storage capacities, are offered to users over communication networks as a cloud-based service. There, demanding computations are outsourced in order to…

Serial-parallel redundancy is a reliable way to ensure service and systems will be available in cloud computing. That method involves making copies of the same system or program, with only one remaining active. When an error occurs, the…

Due to the pervasive diffusion of personal mobile and IoT devices, many ``smart environments'' (e.g., smart cities and smart factories) will be, among others, generators of huge amounts of data. Currently, this is typically achieved through…

In most PUF-based authentication schemes, a central server is usually engaged to verify the response of the device's PUF to challenge bit-streams. However, the server availability may be intermittent in practice. To tackle such an issue,…

The ability to express a program as a hierarchical composition of parts is an essential tool in managing the complexity of software and a key abstraction this provides is to separate the representation of data from the computation. Many…

With the proliferation of edge AI applications, satisfying user quality of experience (QoE) requirements, such as model inference latency, has become a first class objective, as these models operate in resource constrained settings and…

Consensus mechanisms are the core of any blockchain system. However, the majority of these mechanisms do not target federated learning directly nor do they aid in the aggregation step. This paper introduces Proof of Reasoning (PoR), a novel…

Sequential computation is well understood but does not scale well with current technology. Within the next decade, systems will contain large numbers of processors with potentially thousands of processors per chip. Despite this, many…

Parallel processing of information plays a critical role in accelerating computation. This includes quantum computers, where parallel processing of quantum information will play a critical role in practical quantum advantage. Here, we…

As the artificial intelligence community advances into the era of large models with billions of parameters, distributed training and inference have become essential. While various parallelism strategies-data, model, sequence, and…

Querying very large RDF data sets in an efficient manner requires a sophisticated distribution strategy. Several innovative solutions have recently been proposed for optimizing data distribution with predefined query workloads. This paper…

In this short paper, we introduce the Ridgeline model, an extension of the Roofline model [4] for distributed systems. The Roofline model targets shared memory systems, bounding the performance of a kernel based on its operational…

In recent IoT (Internet of Things) and Web 2.0 technologies, a critical problem arises with respect to storing and processing the large amount of collected data. In this paper we develop and evaluate distributed infrastructures for storing…