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Parallel Performance Measurement of Heterogeneous Parallel Systems with GPUs

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Outgoing claims: the papers this work cites, builds on, or argues with.

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The Vampir Performance Analysis Tool-Set
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Collecting Performance Data with PAPI-C
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Comprehensive Performance Tracking with Vampir 7
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Towards dense linear algebra for hybrid GPU accelerated manycore systems
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Non-intrusive Performance Analysis of Parallel Hardware Accelerated Applications on Hybrid Architectures
inferredcites →https://doi.org/10.1145/1735688.1735702openalex-snapshot
The Scalable Heterogeneous Computing (SHOC) benchmark suite
inferredcites →https://doi.org/10.1145/1810085.1810105openalex-snapshot
An experimental approach to performance measurement of heterogeneous parallel applications using CUDA
inferredcites →https://doi.org/10.1177/109434200001400303openalex-snapshot
A Portable Programming Interface for Performance Evaluation on Modern Processors
inferredcites →https://doi.org/10.1177/1094342006064482openalex-snapshot
The Tau Parallel Performance System
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Programming Massively Parallel Processors. A Hands-on Approach
inferredcites →https://doi.org/10.3233/978-1-60750-530-3-341openalex-snapshot
Performance Measurement of Applications with GPU Acceleration using CUDA

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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