User-Defined Tensor Data Analysis (Record no. 185709)
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000 -LEADER | |
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fixed length control field | 05528nam a22005775i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-030-70750-7 |
003 - CONTROL NUMBER IDENTIFIER | |
control field | DE-He213 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20240423130147.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
fixed length control field | cr nn 008mamaa |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 210929s2021 sz | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9783030707507 |
-- | 978-3-030-70750-7 |
024 7# - OTHER STANDARD IDENTIFIER | |
Standard number or code | 10.1007/978-3-030-70750-7 |
Source of number or code | doi |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
Classification number | QA76.9.D3 |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | UN |
Source | bicssc |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | COM021000 |
Source | bisacsh |
072 #7 - SUBJECT CATEGORY CODE | |
Subject category code | UN |
Source | thema |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 005.74 |
Edition number | 23 |
100 1# - MAIN ENTRY--PERSONAL NAME | |
Personal name | Dong, Bin. |
Relator term | author. |
Relator code | aut |
-- | http://id.loc.gov/vocabulary/relators/aut |
245 10 - TITLE STATEMENT | |
Title | User-Defined Tensor Data Analysis |
Medium | [electronic resource] / |
Statement of responsibility, etc | by Bin Dong, Kesheng Wu, Suren Byna. |
250 ## - EDITION STATEMENT | |
Edition statement | 1st ed. 2021. |
264 #1 - | |
-- | Cham : |
-- | Springer International Publishing : |
-- | Imprint: Springer, |
-- | 2021. |
300 ## - PHYSICAL DESCRIPTION | |
Extent | XII, 101 p. 23 illus. |
Other physical details | online resource. |
336 ## - | |
-- | text |
-- | txt |
-- | rdacontent |
337 ## - | |
-- | computer |
-- | c |
-- | rdamedia |
338 ## - | |
-- | online resource |
-- | cr |
-- | rdacarrier |
347 ## - | |
-- | text file |
-- | |
-- | rda |
490 1# - SERIES STATEMENT | |
Series statement | SpringerBriefs in Computer Science, |
International Standard Serial Number | 2191-5776 |
505 0# - FORMATTED CONTENTS NOTE | |
Formatted contents note | 1. Introduction -- 1.1 Lessons from Big Data Systems -- 1.2 Data Model -- 1. 3 Programming Model High-Performance Data Analysis for Science -- 2. FasTensor Programming Model -- 2.1 Introduction to Tensor Data Model -- 2.2 FasTensor Programming Model -- 2.2.1 Stencils -- 2.2.2 Chunks -- 2.2.3 Overlap -- 2.2.4 Operator: Transform -- 2.2.5 FasTensor Execution Engine -- 2.2.6 FasTensor Scientific Computing Use Cases -- 2.3 Summary -- Illustrated FasTensor User Interface -- 3.1 An Example -- 3.2 The Stencil Class -- 3.2.1 Constructors of the Stencil -- 3.2.2 Parenthesis operator () and ReadPoint -- 3.2.3 SetShape and GetShape -- 3.2.4 SetValue and GetValue -- 3.2.5 ReadNeighbors and WriteNeighbors -- 3.2.6 GetOffsetUpper and GetOffsetLower -- 3.2.7 GetChunkID -- 3.2.8 GetGlobalIndex and GetLocalIndex -- 3.2.9 Exercise of the Stencil class -- 3.3 The Array Class -- 3.3.1 Constructors of Array -- 3.3.2 SetChunkSize, SetChunkSizeByMem, SetChunkSizeByDim, and GetChunkSize -- 3.3.3 SetOverlapSize, SetOverlapSizeByDetection,GetOverlapSize, SetOverlapPadding, and SyncOverlap -- 3.3.4 Transform -- 3.3.5 SetStride and GetStride -- 3.3.6 AppendAttribute, InsertAttribute, GetAttribute and EraseAttribute -- 3.3.7 SetEndpoint and GetEndpoint -- 3.3.8 ControlEndpoint -- 3.3.9 -- ReadArray and WriteArray -- 3.3.10 SetTag and GetTag -- 3.3.11 GetArraySize and SetArraySize -- 3.3.12 Backup and Restore -- 3.3.13 CreateVisFile -- 3.3.14 ReportCost -- 3.3.15 EP_DIR Endpoint -- 3.3.16 EP_HDF5 and Other Endpoints -- Other Functions in FasTensor -- 3.4.1 FT_Init -- 3.4.2 FT_Finalize -- 3.4.3 Data types in FasTensor -- 4. FasTensor in Real Scientific Applications -- 4.1 DAS: Distributed Acoustic Sensing -- 4.2 VPIC: Vector Particle-In-Cell -- Appendix -- A.1 Installation Guide of FasTensor -- A.2 How to Develop a New Endpoint Protocol -- Alphabetical Index -- Bibliography -- References. . |
520 ## - SUMMARY, ETC. | |
Summary, etc | Ths SpringerBrief introduces FasTensor, a powerful parallel data programming model developed for big data applications. This book also provides a user's guide for installing and using FasTensor. FasTensor enables users to easily express many data analysis operations, which may come from neural networks, scientific computing, or queries from traditional database management systems (DBMS). FasTensor frees users from all underlying and tedious data management tasks, such as data partitioning, communication, and parallel execution. This SpringerBrief gives a high-level overview of the state-of-the-art in parallel data programming model and a motivation for the design of FasTensor. It illustrates the FasTensor application programming interface (API) with an abundance of examples and two real use cases from cutting edge scientific applications. FasTensor can achieve multiple orders of magnitude speedup over Spark and other peer systems in executing big data analysis operations. FasTensor makes programming for data analysis operations at large scale on supercomputers as productively and efficiently as possible. A complete reference of FasTensor includes its theoretical foundations, C++ implementation, and usage in applications. Scientists in domains such as physical and geosciences, who analyze large amounts of data will want to purchase this SpringerBrief. Data engineers who design and develop data analysis software and data scientists, and who use Spark or TensorFlow to perform data analyses, such as training a deep neural network will also find this SpringerBrief useful as a reference tool. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Database management. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Big data. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Engineering |
General subdivision | Data processing. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Machine learning. |
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Database Management. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Big Data. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Data Engineering. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Machine Learning. |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Wu, Kesheng. |
Relator term | author. |
Relator code | aut |
-- | http://id.loc.gov/vocabulary/relators/aut |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Byna, Suren. |
Relator term | author. |
Relator code | aut |
-- | http://id.loc.gov/vocabulary/relators/aut |
710 2# - ADDED ENTRY--CORPORATE NAME | |
Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY | |
Title | Springer Nature eBook |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Printed edition: |
International Standard Book Number | 9783030707491 |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
Display text | Printed edition: |
International Standard Book Number | 9783030707514 |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
Uniform title | SpringerBriefs in Computer Science, |
-- | 2191-5776 |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | <a href="https://doi.org/10.1007/978-3-030-70750-7">https://doi.org/10.1007/978-3-030-70750-7</a> |
912 ## - | |
-- | ZDB-2-SCS |
912 ## - | |
-- | ZDB-2-SXCS |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks-CSE-Springer |
No items available.