Article-Journal

Counting and listing triangles in graphs is a fundamental task in network analysis, supporting applications such as community …

Connectomics, a subfield of neuroscience, reconstructs structural and functional brain maps at synapse-level resolution. These complex …

Understanding information flow in the brain can be facilitated by arranging neurons in the fly connectome to form a maximally …

We study quantum interior point methods (QIPMs) for second-order cone programming (SOCP), guided by the example use case of portfolio …

The suffix array is a crucial data structure for efficient string analysis. Over the course of twenty-six years, sequential suffix …

Given an undirected, weighted graph, the minimum spanning tree (MST)is a tree that connects all of the vertices of the graph with …

Network analysis defines a number of centrality measures to identify the most central nodes in a network. Fast computation of those …

Detecting anomalies with high accuracy and real time from large amounts of streaming data is a challenge for many real-world …

Identifying anomalies, especially weak anomalies in constantly changing targets, is more difficult than in stable targets. In this …

David A. Bader built the first Linux Supercomputer.

Data from emerging applications, such as cybersecurity and social networking, can be abstracted as graphs whose edges are updated …

Due to the limited capacity of GPU memory, the majority of prior work on graph applications on GPUs has been restricted to graphs of …

Parallel Alternating Criteria Search (PACS) relies on the combination of computer parallelism and Large Neighborhood Searches to …

Graphs that model social networks, numerical simulations, and the structure of the Internet are enormous and cannot be manually …

We present a parallel large neighborhood search framework for finding high quality primal solutions for general mixed-integer programs …

A variety of large datasets, such as social networks or biological data, can be represented as graphs. A common query in graph analysis …

Many real-world datasets can be represented as graphs. Using iterative solvers to approximate graph centrality measures allows us to …

We present a parallel local search approach for obtaining high quality solutions to the Fixed Charge Multicommodity Network Flow …

Breadth-First Search (BFS) is widely used in real-world applications including computational biology, social networks, and electronic …

Presents the introductory editorial for this issue of the publication.

Presents the introductory editorial for this issue of the publication.

The edit distance under the DCJ model can be computed in linear time for genomes with equal content or with Indels. But it becomes …

Graphs and networks are prevalent in modeling relational datasets from many fields of research. By using iterative solvers to …

Analyzing massive graphs poses challenges due to the vast amount of data available. Extracting smaller relevant subgraphs allows for …

We describe a family of power models that can capture the nonuniform power effects of speed scaling among homogeneous cores on …

Many common methods for data analysis rely on linear algebra. We provide new results connecting data analysis error to numerical …

Simulating binary black hole (BBH) systems are a computationally intensive problem and it can lead to great scientific discovery. How …

Welcome to this year’s first issue of IEEE Transactions on Parallel and Distributed Systems (TPDS). The author is privileged to …

This installment of Computer’s series highlighting the work published in IEEE Computer Society journals comes from IEEE …

The edit distance under the DCJ model can be computed in linear time for genomes with equal content or with Indels. But it becomes …

Multicore processors have become an integral part of modern large-scale and high-performance parallel and distributed computing …

A variety of massive datasets, such as social networks and biological data, are represented as graphs that reveal underlying …

This paper contributes a method for combining sparse parallel graph algorithms with dense parallel linear algebra algorithms in order …

Presents the introductory editorial for this issue of the publication

The analysis of graphs has become increasingly important to a wide range of applications. Graph analysis presents a number of unique …

Many common methods for data analysis rely on linear algebra. We provide new results connecting data analysis error to numerical …

Reports on the current state of the IEEE Transactions on Computers.

Serving as cache disks, flash-based solid-state drives (SSDs) can significantly boost the performance of read-intensive applications. …

It is our view that the state of the art in constructing a large collection of graph algorithms in terms of linear …

I am excited with my new role as incoming Editor-in-Chief (EiC) of IEEE Transactions on Parallel and Distributed Systems (TPDS) and …

With the proliferation of large irregular sparse relational datasets, new storage and analysis platforms have arisen to fill gaps in …

Betweenness centrality is a graph analytic that states the importance of a vertex based on the number of shortest paths that it is on. …

The digital world has given rise to massive quantities of data that include rich semantic and complex networks. A social graph, for …

The study of genomes has been revolutionized by sequencing machines that output many short overlapping substrings (called reads). The …

The problem of finding the median of three genomes is the key process in building the most parsimonious phylogenetic trees from genome …

DNA sequence analysis is fundamental to life science research. The rapid development of next generation sequencing (NGS) technologies, …

The recent switch to multicore processors brought a dramatic change that affects a large spectrum of systems from embedded and …

Reducing energy consumption has been an important design issue for large-scale streaming media storage systems. Existing energy …

Background Accurate and efficient RNA secondary structure prediction remains an important open problem in computational molecular …

Maximum parsimony (MP) methods aim to reconstruct the phylogeny of extant species by finding the most parsimonious evolutionary …

Modern multicore and manycore systems have the strong potential to deliver both high performance and high power efficiency. The large …

In this paper, we present a GPU-based sorting algorithm, GPUMemSort, which achieves high performance in sorting large-scale in-memory …

The 12 papers in this special issue on high-performance computing with accelerators discuss a range of different accelerator …

The Cell Broad Engine (BE) Processor has unique memory access architecture besides its powerful computing engines. Many …

Discrete transforms are of primary importance and fundamental kernels in many computationally intensive scientific applications. In …

By 2010, the global options and equity markets will average over 128 billion messages per day, amounting to trillions of dollars in …

Due to fundamental physical limitations and power constraints, we are witnessing a paradigm shift in commodity microprocessor …

A regeneration-theory approach is undertaken to analytically characterize the average overall completion time in a distributed system. …

The Sony–Toshiba–IBM Cell Broadband Engine (Cell/B.E.) is a heterogeneous multicore architecture that consists of a traditional …

In this paper, we address the problem of multiple sequence alignment (MSA) for handling very large number of proteins sequences on …

The computation of ever larger as well as more accurate phylogenetic (evolutionary) trees with the ultimate goal to compute the tree of …

Irregular parallel algorithms pose a significant challenge for achieving high performance because of the difficulty predicting memory …

One of the main objectives of the DARPA High Productivity Computing Systems (HPCS) program is to reassess the way we define and measure …

Minimum spanning tree (MST) is one of the most studied combinatorial problems with practical applications in VLSI layout, wireless …

The ability to provide uniform shared-memory access to a significant number of processors in a single SMP node brings us much closer to …

We propose a framework for measuring the productivity of high performance computing (HPC) systems, based on common economic definitions …

A common statistical problem is that of finding the median element in a set of data. This paper presents an efficient randomized …

Understanding evolution and the basic structure and function of proteins are two grand challenge problems in biology that can be solved …

Srinivas Aluru is an associate professor and Associate Chair for Graduate Education in the Department of Electrical and Computer …

In this work, a generalized topology of block shift networks (BSNs), named generalized block shift network (GBSN), is propose or …

A phylogeny is the evolutionary history of a group of organisms; systematists (and other biologists) attempt to reconstruct this …

Hannenhalli and Pevzner gave the first polynomial-time algorithm for computing the inversion distance between two signed permutations, …

Global and regional land cover studies need to apply complex models on selected subsets of large volumes of multi-sensor and …

Raw remotely sensed satellite data have to be processed andmapped into a standard projection in order to produce a multi-temporal data …

At first thought, one may not realize the need for a special issue of Parallel and Distributed Computing Practices focused on Cluster …

We describe a methodology for developing high performance programs running on clusters of SMP nodes. The SMP cluster programming …

We introduce a new deterministic parallel sorting algorithm for distributed memory machines based on the regular sampling approach. The …

Previous schemes for sorting on general-purpose parallel machines have had to choose between poor load balancing and irregular …

This paper presents efficient and portable implementations of a powerful image enhancement process, the Symmetric Neighborhood Filter …

This paper presents efficient and portable implementations of two useful primitives in image processing algorithms, histogramming and …

A fundamental challenge for parallel computing is to obtain high-level, architecture independent, algorithms which efficiently execute …

This article introduces scalable data parallel algorithms for image processing. Focusing on Gibbs and Markov random field model …