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Locality-Aware Mapping of Nested Parallel Patterns on GPUs
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/3-540-45937-5_14openalex-snapshot
StreamIt: A Language for Streaming Applications
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Harnessing the Multicores: Nested Data Parallelism in Haskell
inferredcites →https://doi.org/10.1007/978-3-540-89740-8_1openalex-snapshot
CUDA-Lite: Reducing GPU Programming Complexity
inferredcites →https://doi.org/10.1007/978-3-642-23397-5_14openalex-snapshot
A Generic Parallel Collection Framework
inferredcites →https://doi.org/10.1016/j.ymeth.2009.04.013openalex-snapshot
Using generalized ensemble simulations and Markov state models to identify conformational states
inferredcites →https://doi.org/10.1109/cgo.2009.20openalex-snapshot
Software Pipelined Execution of Stream Programs on GPUs
inferredcites →https://doi.org/10.1109/iiswc.2009.5306797openalex-snapshot
Rodinia: A benchmark suite for heterogeneous computing
inferredcites →https://doi.org/10.1109/pact.2011.15openalex-snapshot
A Heterogeneous Parallel Framework for Domain-Specific Languages
inferredcites →https://doi.org/10.1145/1555754.1555775openalex-snapshot
An analytical model for a GPU architecture with memory-level and thread-level parallelism awareness
inferredcites →https://doi.org/10.1145/1693453.1693470openalex-snapshot
An adaptive performance modeling tool for GPU architectures
inferredcites →https://doi.org/10.1145/1806596.1806606openalex-snapshot
A GPGPU compiler for memory optimization and parallelism management
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Accelerating CUDA graph algorithms at maximum warp
inferredcites →https://doi.org/10.1145/1993316.1993516openalex-snapshot
Automatic CPU-GPU communication management and optimization
inferredcites →https://doi.org/10.1145/2254064.2254066openalex-snapshot
Compiling a high-level language for GPUs
inferredcites →https://doi.org/10.1145/2364527.2364563openalex-snapshot
Nested data-parallelism on the gpu
inferredcites →https://doi.org/10.1145/2400682.2400713openalex-snapshot
Polyhedral parallel code generation for CUDA
inferredcites →https://doi.org/10.1145/2500365.2500595openalex-snapshot
Optimising purely functional GPU programs
inferredcites →https://doi.org/10.4230/lipics.fsttcs.2008.1769openalex-snapshot
Harnessing the Multicores: Nested Data Parallelism in Haskell
inferredcites →https://doi.org/10.48550/arxiv.1106.5730openalex-snapshot
HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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An Analytical Model-Based Auto-tuning Framework for Locality-Aware Loop Scheduling
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LIFT: A functional data-parallel IR for high-performance GPU code generation
inferred← citeshttps://doi.org/10.1109/hpca.2019.00038openalex-snapshot
Poly: Efficient Heterogeneous System and Application Management for Interactive Applications
inferred← citeshttps://doi.org/10.1109/ipdps.2016.36openalex-snapshot
Eliminating Intra-Warp Load Imbalance in Irregular Nested Patterns via Collaborative Task Engagement
inferred← citeshttps://doi.org/10.1109/isca.2016.57openalex-snapshot
LaPerm: Locality Aware Scheduler for Dynamic Parallelism on GPUs
inferred← citeshttps://doi.org/10.1109/ispass.2019.00040openalex-snapshot
mRNA: Enabling Efficient Mapping Space Exploration for a Reconfiguration Neural Accelerator
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Plasticine: A Reconfigurable Accelerator for Parallel Patterns
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An Efficient Vectorization Approach to Nested Thread-level Parallelism for CUDA GPUs
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CRAT: Enabling Coordinated Register Allocation and Thread-Level Parallelism Optimization for GPUs
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Enabling coordinated register allocation and thread-level parallelism optimization for GPUs
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Have abstraction and eat performance, too: optimized heterogeneous computing with parallel patterns
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Performance portable GPU code generation for matrix multiplication
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Generating Configurable Hardware from Parallel Patterns
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Matrix multiplication beyond auto-tuning
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Designing a Tunable Nested Data-Parallel Programming System
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