Search Results - computer program nesting _ processing.

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  1. 1
    Published 2017
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  2. 2
    Published 1991
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    by Harrop, Jon D.
    Published 2008
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    by Barlas, Gerassimos
    Published 2015
    Table of Contents: ...Chapter 8: Load balancing -- 8.1 Introduction -- 8.2 Dynamic load balancing: the Linda legacy -- 8.3 Static Load Balancing: The Divisible LoadTheory Approach -- 8.3.1 Modeling Costs -- 8.3.2 Communication Configuration -- 8.3.3 Analysis -- 8.3.3.1 N-Port, Block-Type, Single-Installment Solution -- 8.3.3.2 One-Port, Block-Type, Single-Installment Solution -- 8.3.4 Summary -- Short Literature Review -- 8.4 DLTlib: A library for partitioning workloads -- 8.5 Case studies -- 8.5.1 Hybrid Computation of a Mandelbrot Set "Movie'':A Case Study in Dynamic Load Balancing -- 8.5.2 Distributed Block Cipher Encryption: A Case Study in Static Load Balancing -- Appendix A: Compiling Qt programs -- A.1 Using an IDE -- A.2 The qmake Utility -- Appendix B: Running MPI programs -- B.1 Preparatory Steps -- B.2 Computing Nodes discovery for MPI Program Deployment -- B.2.1 Host Discovery with the nmap Utility -- B.2.2 Automatic Generation of a Hostfile -- Appendix C: Time measurement -- C.1 Introduction -- C.2 POSIX High-Resolution Timing -- C.3 Timing in Qt -- C.4 Timing in OpenMP -- C.5 Timing in MPI -- C.6 Timing in CUDA -- Appendix D: Boost.MPI -- D.1 Mapping from MPI C to Boost.MPI -- Appendix E: Setting up CUDA -- E.1 Installation -- E.2 Issues with GCC -- E.3 Running CUDA without an Nvidia GPU -- E.4 Running CUDA on Optimus-Equipped Laptops -- E.5 Combining CUDA with Third-Party Libraries -- Appendix F: DLTlib -- F.1 DLTlib Functions -- F.1.1 Class Network: Generic Methods -- F.1.2 Class Network: Query Processing -- F.1.3 Class Network: Image Processing -- F.1.4 Class Network: Image Registration -- F.2 DLTlib Files -- Glossary -- Bibliography -- Index....
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    Published 2021
    Table of Contents: ...Compilers, Tools and Environments -- ALONA: Automatic Loop Nest Approximation with Reconstruction and Space Pruning -- Automatic low-overhead load-imbalance detection in MPI applications -- Performance and Power Modeling, Prediction and Evaluation -- Trace-driven Workload Generation and Execution -- Bilas Update on the Asymptotic Optimality of LPT -- E2EWatch: An End-to-end Anomaly Diagnosis Framework for Production HPC Systems -- Scheduling and Load Balancing -- Collaborative GPU Preemption via Spatial Multitasking for Efficient GPU Sharing -- A Fixed-Parameter Algorithm for Scheduling Unit dependent Tasks with Unit Communication Delays -- Plan-based Job Scheduling for Super computers with Shared Burst Buffers -- Taming Tail Latency in Key-Value Stores: a Scheduling Perspective -- A log-linear(2+5/6)-approximation algorithm for parallel machine scheduling with a single orthogonal resource -- An MPI-Parallel Algorithm for Mapping Complex Networks onto Hierarchical Architectures -- Pipelined Model Parallelism: Complexity Results and Memory Considerations -- Data Management, Analytics and Machine Learning -- Efficient and Systematic Partitioning of Large and Deep Neural Networks for Parallelization -- A GPU Architecture Aware Fine-Grain Pruning Technique for Deep Neural Networks -- Towards Flexible and Compiler-Friendly Layer Fusion for CNNs on Multicore CPUs -- Smart Distributed Data Sets for Stream Processing -- Cluster, Cloud and Edge Computing -- Colony: Parallel Functions as a Service on the Cloud-Edge Continuum -- Horizontal Scaling in Cloud using Contextual Bandits -- Geo-Distribute Cloud Application at the Edge -- A Fault Tolerant and Deadline Constrained Sequence Alignment Application on Cloud-based Spot GPU Instances -- Sustaining Performance While Reducing Energy Consumption: A Control Theory Approach -- Theory and Algorithms for Parallel and Distributed Processing -- Algorithm design for Tensor Units -- A Scalable Approximation Algorithm for Weighted Longest Common Subsequence -- TSL Queue: An E‑cient Lock-free Design for Priority Queues -- G-Morph: Induced Subgraph Isomorphism Search of Labeled Graphs on a GPU -- Parallel and Distributed Programming, Interfaces, and Languages -- Accelerating Graph Applications Using Phased Transactional Memory -- Efficient GPU Computation using Task Graph Parallelism -- Towards High Performance Resilience using Performance Portable Abstractions -- Enhancing Load-Balancing of MPI Applications with Workshare -- Particle-In-Cell Simulation using Asynchronous Tasking -- Multicore and Manycore Parallelism -- Exploiting co-execution with one API: heterogeneity from a modern perspective -- Parallel Numerical Methods and Applications -- Designing a 3D Parallel Memory-Aware Lattice Boltzmann Algorithm on Manycore Systems -- Fault-tolerant LU factorization is low cost -- Mixed Precision Incomplete and Factorized Sparse Approximate Inverse Preconditioning on GPUs -- Outsmarting the Atmospheric Turbulence for Ground-Based Telescopes Using the Stochastic Levenberg-Marquardt Method -- GPU Accelerated Mahalanobis-average Hierarchical Clustering Analysis -- High performance architectures and accelerators -- PrioRAT: Criticality-Driven Prioritization Inside the On-Chip Memory Hierarchy -- Optimized Implementation of the HPCG Benchmark on Recongurable Hardware....
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    by Guta, Gabor
    Published 2022
    Table of Contents: ...Characters with Special Meaning -- Python Standards -- Object Diagram Notation -- Key Takeaways -- Chapter 2: The Function: Programs as a Series of Statements -- Calling a Function -- Side Effects of Functions -- Function Arguments -- Defining a Function -- Keyword Arguments -- Visibility of Names -- Functions as Parameters -- Definitions of Nested Functions -- Functions in Practice -- Advanced Details -- Namespace and Scope -- Positional-Only and Keyword-Only Parameters -- Variable Number of Arguments -- Lambda Expression -- Decorator -- Yield Statement and Asynchronous Functions...
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    by Teubner, Jens (Jens Thilo)
    Published 2013
    Table of Contents: ...Introduction -- 1.1 Moore's law and transistor-speed scaling -- 1.2 Memory wall and Von Neumann bottleneck -- 1.3 Power wall -- 1.4 Multicore CPUs and GPUs -- 1.5 Specialized hardware -- 1.6 Field-programmable gate arrays (FPGAs) -- 1.7 FPGAs for data processing -- 1.7.1 Stream processing -- 1.7.2 Big data -- 1.7.3 Cloud computing -- 1.7.4 Security --...
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