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Languages and Compilers for Parallel Computing

Overview of attention for book
Cover of 'Languages and Compilers for Parallel Computing'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Optimistic Parallelism on GPUs
  3. Altmetric Badge
    Chapter 2 Directive-Based Compilers for GPUs
  4. Altmetric Badge
    Chapter 3 GLES: A Practical GPGPU Optimizing Compiler Using Data Sharing and Thread Coarsening
  5. Altmetric Badge
    Chapter 4 Evaluating Performance Portability of OpenACC
  6. Altmetric Badge
    Chapter 5 NAS Parallel Benchmarks for GPGPUs Using a Directive-Based Programming Model
  7. Altmetric Badge
    Chapter 6 Understanding Co-run Degradations on Integrated Heterogeneous Processors
  8. Altmetric Badge
    Chapter 7 Simultaneous Inspection: Hiding the Overhead of Inspector-Executor Style Dynamic Parallelization
  9. Altmetric Badge
    Chapter 8 Tiled Linear Algebra a System for Parallel Graph Algorithms
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    Chapter 9 An Approach for Proving the Correctness of Inspector/Executor Transformations
  11. Altmetric Badge
    Chapter 10 Fast Automatic Heuristic Construction Using Active Learning
  12. Altmetric Badge
    Chapter 11 Jagged Tiling for Intra-tile Parallelism and Fine-Grain Multithreading
  13. Altmetric Badge
    Chapter 12 Languages and Compilers for Parallel Computing
  14. Altmetric Badge
    Chapter 13 Memory Management Techniques for Exploiting RDMA in PGAS Languages
  15. Altmetric Badge
    Chapter 14 Change Detection Based Parallelism Mapping: Exploiting Offline Models and Online Adaptation
  16. Altmetric Badge
    Chapter 15 Automatic Streamization of Image Processing Applications
  17. Altmetric Badge
    Chapter 16 Evaluation of Automatic Power Reduction with OSCAR Compiler on Intel Haswell and ARM Cortex-A9 Multicores
  18. Altmetric Badge
    Chapter 17 \(\pi \) Abstraction: Parallelism-Aware Array Data Flow Analysis for OpenMP
  19. Altmetric Badge
    Chapter 18 Static Approximation of MPI Communication Graphs for Optimized Process Placement
  20. Altmetric Badge
    Chapter 19 Automatic Parallelism Through Macro Dataflow in MATLAB
  21. Altmetric Badge
    Chapter 20 Re-Engineering Compiler Transformations to Outperform Database Query Optimizers
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    Chapter 21 Systematic Debugging of Concurrent Systems Using Coalesced Stack Trace Graphs
  23. Altmetric Badge
    Chapter 22 LightPlay: Efficient Replay with GPUs
  24. Altmetric Badge
    Chapter 23 Exploring and Evaluating Array Layout Restructuring for SIMDization
  25. Altmetric Badge
    Chapter 24 Unification of Static and Dynamic Analyses to Enable Vectorization
  26. Altmetric Badge
    Chapter 25 Efficient Exploitation of Hyper Loop Parallelism in Vectorization
Attention for Chapter 12: Languages and Compilers for Parallel Computing
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (56th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

wikipedia
2 Wikipedia pages

Citations

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2 Dimensions

Readers on

mendeley
9 Mendeley
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Chapter title
Languages and Compilers for Parallel Computing
Chapter number 12
Book title
Languages and Compilers for Parallel Computing
Published in
Lecture notes in computer science, September 2014
DOI 10.1007/978-3-319-17473-0_12
Book ISBNs
978-3-31-917472-3, 978-3-31-917473-0
Authors

Mani Zandifar, Nathan Thomas, Nancy M. Amato, Lawrence Rauchwerger

Editors

James Brodman, Peng Tu

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 11%
Unknown 8 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 67%
Unspecified 1 11%
Student > Bachelor 1 11%
Student > Doctoral Student 1 11%
Readers by discipline Count As %
Computer Science 7 78%
Unspecified 1 11%
Engineering 1 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 June 2021.
All research outputs
#7,496,019
of 22,914,829 outputs
Outputs from Lecture notes in computer science
#2,487
of 8,129 outputs
Outputs of similar age
#79,985
of 246,672 outputs
Outputs of similar age from Lecture notes in computer science
#92
of 232 outputs
Altmetric has tracked 22,914,829 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,129 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 54% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 246,672 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.
We're also able to compare this research output to 232 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.