Value-Compressed Sparse Column (VCSC): Sparse Matrix Storage for Redundant Data

Compressed Sparse Column (CSC) and Coordinate (COO) are popular compression formats for sparse matrices. However, both CSC and COO are general purpose and cannot take advantage of any of the properties of the data other than sparsity, such as data redundancy. Highly redundant sparse data is common in many machine learning applications, such as genomics, and is often too large for in-core computation using conventional sparse storage formats. In this paper, we present two extensions to CSC: (1) Value-Compressed Sparse Column (VCSC) and (2) Index- and Value-Compressed Sparse Column (IVCSC). VCSC takes advantage of high redundancy within a column to further compress data up to 3-fold over COO and 2.25-fold over CSC, without significant negative impact to performance characteristics. IVCSC extends VCSC by compressing index arrays through delta encoding and byte-packing, achieving a 10-fold decrease in memory usage over COO and 7.5-fold decrease over CSC. Our benchmarks on simulated and real data show that VCSC and IVCSC can be read in compressed form with little added computational cost. These two novel compression formats offer a broadly useful solution to encoding and reading redundant sparse data

SMP: A solid modeling program version 2.0

The Solid Modeling Program (SMP) provides the capability to model complex solid objects through the composition of primitive geometric entities. In addition to the construction of solid models, SMP has extensive facilities for model editing, display, and analysis. The geometric model produced by the software system can be output in a format compatible with existing analysis programs such as PATRAN-G. The present version of the SMP software supports six primitives: boxes, cones, spheres, paraboloids, tori, and trusses. The details for creating each of the major primitive types is presented. The analysis capabilities of SMP, including interfaces to existing analysis programs, are discussed

Proceedings of the Eighth Annual Software Engineering Workshop

The four major topics of discussion included: the NASA Software Engineering Laboratory, software testing, human factors in software engineering and software quality assessment. As in the past years, there were 12 position papers presented (3 for each topic) followed by questions and very heavy participation by the general audience

Annotated bibliography of Software Engineering Laboratory literature

This document is an annotated bibliography of technical papers, documents, and memorandums produced by or related to the Software Engineering Laboratory. Nearly 200 publications are summarized. These publications cover many areas of software engineering and range from research reports to software documentation. This document has been updated and reorganized substantially since the original version (SEL-82-006, November 1982). All materials have been grouped into eight general subject areas for easy reference: the Software Engineering Laboratory; the Software Engineering Laboratory: software development documents; software tools; software models; software measurement; technology evaluations; Ada technology; and data collection. This document contains an index of these publications classified by individual author

Annotated bibliography of software engineering laboratory literature

This document is an annotated bibliography of technical papers, documents, and memorandums produced by or related to the Software Engineering Laboratory. Nearly 200 publications are summarized. These publications cover many areas of software engineering and range from research reports to software documentation. This document has been updated and reorganized substantially since the original version (SEL-82-006, November 1982). All materials have been grouped into eight general subject areas for easy reference: (1) The Software Engineering Laboratory; (2) The Software Engineering Laboratory: Software Development Documents; (3) Software Tools; (4) Software Models; (5) Software Measurement; (6) Technology Evaluations; (7) Ada Technology; and (8) Data Collection. This document contains an index of these publications classified by individual author

Monitor Newsletter January 11, 1988

Official Publication of Bowling Green State University for Faculty and Staffhttps://scholarworks.bgsu.edu/monitor/1902/thumbnail.jp

A Consensus on the Definition and Knowledge Base for Computer Graphics

Despite several decades of historical innovation, measurable impacts, and multiple specializations the existing knowledge base for Computer Graphics (CG) lacks consensus, and numerous definitions for it have been published based on distinct contexts. Disagreement among post-secondary academics has divided CG programs into three contextual areas that emphasize different topics. This division has resulted in the decontextualization of CG education, and CG programs now face several challenges in meeting the needs of industry. Employing the Delphi Method, this investigation explored the perceptions among post-secondary educators and industry professionals about the definition of CG and how it is identified in terms of characteristics and context. The outcomes of this investigation identified CG in the technological paradigm, and provided a road map towards a true definition and distinct knowledge base necessary for establishing CG as a formal computing discipline

Flight dynamics system software development environment (FDS/SDE) tutorial

A sample development scenario using the Flight Dynamics System Software Development Environment (FDS/SDE) is presented. The SDE uses a menu-driven, fill-in-the-blanks format that provides online help at all steps, thus eliminating lengthy training and allowing immediate use of this new software development tool

TikTokin suositusjärjestelmän tutkinta haamuhenkilöillä

The content we see is increasingly determined by ever more advanced recommender systems, and popular social media platform TikTok represents the forefront of this development (See Chapter 1). There has been much speculation about the workings of these recommender systems, but precious little systematic, controlled study (See Chapter 2). To improve our understanding of these systems, I developed sock puppet bots that consume content on TikTok as a normal user would (See Chapter 3). This allowed me to run controlled experiments to see how the TikTok recommender system would respond to sock puppets exhibiting different behaviors and preferences in a Finnish context, and how this would differ from the results obtained by earlier investigations (See Chapter 4). This research was done as part of a journalistic investigation in collaboration with Long Play. I found that TikTok appears to have adjusted their recommender system to personalize content seen by users to a much lesser degree, likely in response to a previous investigation by the WSJ. However, I came to the conclusion that, while sock puppet audits can be useful, they are not a sufficiently scalable solution to algorithm governance, and other types of audits with more internal access are needed (See Chapter 5)