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There is a critical DoD need for reliable acoustic vector sensor arrays with high signal dynamic range, low self-noise, and are capable of operating effectively across all ocean depths to detect, classify and localize low-level signals. Deployment below the critical depth allows the vertical line of vector sensors to exploit the Reliable Acoustic Path (RAP), and enables monitoring a large volume o ...

This proposal describes a program to substantially accelerate graph analytic algorithms by leveraging many-core computation, and to allow seamless use of these accelerated implementations within popular graph ecosystems. We will (1) improve, adapt, and extend our Gunrock multi-GPU graph analytic engine with additional algorithms -- including tailored randomized algorithms for community detection a ...

Intelligent Fiber Optic Systems Corporation (IFOS) and Stanford University (SU) intend to demonstrate a 150 meter long, 12-sensor depth insensitive pressure sensor array. The overall goal of this SBIR project is to develop an innovative, passive, low-power array of acoustic pressure and vector sensors that can operate effectively across all ocean depths to detect, classify, and localize low-level ...

Theoretical computing speeds have increased dramatically in the last decade with chip advances, including Graphics Processor Units (GPUs).In practice, however, these gains have not been realized, largely due to the accompanying high development costs due to the need for multiple code bases to take advantage of the various chips and their variants.The proposed project addresses these issues from bo ...

Graph analytics platforms are widely deployed across diverse domains to analyze large, unstructured and semi-structured data-sets. While existing tools are clearly effective, there is a persistent need to perform deeper analyses on larger data-sets and retrieve information more quickly. Low data-locality and a high communication to compute ratio means that existing distributed frameworks are unlik ...

To address the Defense Advanced Projects Research Agencys (DARPAs) need for next-generation computing systems for processing large scale graph datasets, Physical Optics Corporation (POC) proposes to develop a new Domain-Aware Self-learning Hardware Accelerated Graph Analytics (DASHGRAPH) system. This proposed solution is based on a new design that utilizes machine learning algorithms in a reconfig ...

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Graphs are an exceptional data structure for representing knowledge and relationships between facts. There are various frameworks for creating, modifying, and traversing graphs in software. These frameworks provide an abstraction over the physical representation of graphs on disk. Usually, the graphs are modeled physically as tables. The schema or layout of these tables significantly impacts the ...

This research effort will develop an OpenCL Shared Virtual Memory (SVM) hardware acceleration Application Programming Interface (API) capable of enabling existing graph analytic APIs (e.g. GraphLab, GraphCT) to leverage a scalable, GPU-based hardware platform to significantly improve the performance of graph analytics including graph traversal and Breadth First Search (BFS). The use of OpenCL pro ...

Cellular automata are computer-theoretical models originally developed by computing pioneer John von Neumann in 1950s to study self-reproduction computing machines. Cellular automata are massively parallel, regularly connected and allow only local data exchanges between cells. Cellular automata computation models map perfectly to modern many-core computing hardware. Opportunities have arrived to ...