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Load-balancing Sparse Matrix Vector Product Kernels on GPUs

https://doi.org/10.1145/3380930
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What this work says

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

inferredcites →https://doi.org/10.1007/978-3-642-11515-8_10openalex-snapshot
Automatically Tuning Sparse Matrix-Vector Multiplication for GPU Architectures
inferredcites →https://doi.org/10.1016/j.compeleceng.2013.11.024openalex-snapshot
A survey on feature selection methods
inferredcites →https://doi.org/10.1016/j.parco.2017.05.006openalex-snapshot
Preconditioned Krylov solvers on GPUs
inferredcites →https://doi.org/10.1109/ipdps.2015.98openalex-snapshot
Optimizing Sparse Matrix Operations on GPUs Using Merge Path
inferredcites →https://doi.org/10.1109/ipdpsw.2019.00088openalex-snapshot
Approximate and Exact Selection on GPUs
inferredcites →https://doi.org/10.1137/1.9780898717891openalex-snapshot
Matlab Guide
inferredcites →https://doi.org/10.1137/130930352openalex-snapshot
A Unified Sparse Matrix Data Format for Efficient General Sparse Matrix-Vector Multiplication on Modern Processors with Wide SIMD Units
inferredcites →https://doi.org/10.1137/s0895479895296689openalex-snapshot
Estimating an Eigenvector by the Power Method with a Random Start
inferredcites →https://doi.org/10.1145/1654059.1654078openalex-snapshot
Implementing sparse matrix-vector multiplication on throughput-oriented processors
inferredcites →https://doi.org/10.1145/1941553.1941590openalex-snapshot
Accelerating CUDA graph algorithms at maximum warp
inferredcites →https://doi.org/10.1145/2717511openalex-snapshot
High-Performance and Scalable GPU Graph Traversal
inferredcites →https://doi.org/10.1145/2751205.2751209openalex-snapshot
CSR5
inferredcites →https://doi.org/10.1145/2950048openalex-snapshot
A Note on Performance Profiles for Benchmarking Software
inferredcites →https://doi.org/10.1145/3017994openalex-snapshot
Sparse Matrix-Vector Multiplication on GPGPUs
inferredcites →https://doi.org/10.1145/3149704.3149767openalex-snapshot
Overcoming Load Imbalance for Irregular Sparse Matrices
inferredcites →https://doi.org/10.1145/3293883.3295712openalex-snapshot
Adaptive sparse tiling for sparse matrix multiplication
inferredcites →https://doi.org/10.1145/3324989.3325719openalex-snapshot
Towards Continuous Benchmarking
inferredcites →https://doi.org/10.1145/76263openalex-snapshot
Proceedings of the 1989 ACM/IEEE conference on Supercomputing - Supercomputing '89
inferredcites →https://doi.org/10.2307/2153507openalex-snapshot
Templates for the Solution of Linear Systems: Building Blocks for Iterative Methods.
inferredcites →https://doi.org/10.5555/3014904.3014982openalex-snapshot
Merge-based parallel sparse matrix-vector multiplication

What points at this work

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

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Block strategy and adaptive storage for sparse matrix–vector multiplication on GPU
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On Higher-performance Sparse Tensor Transposition
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Evaluating the Performance of NVIDIA’s A100 Ampere GPU for Sparse and Batched Computations
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AmgT: Algebraic Multigrid Solver on Tensor Cores
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Mille-feuille: A Tile-Grained Mixed Precision Single-Kernel Conjugate Gradient Solver on GPUs
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Accelerated Atomistic Kinetic Monte Carlo Simulations of Resistive Memory Arrays
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Two-stage Asynchronous Iterative Solvers for multi-GPU Clusters
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Shifting Between Compute and Memory Bounds: A Compression-Enabled Roofline Model
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FastLoad: Speeding Up Data Loading of Both Sparse Matrix and Vector for SpMV on GPUs
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Optimization of Large-Scale Sparse Matrix-Vector Multiplication on Multi-GPU Systems
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LiteForm: Lightweight and Automatic Format Composition for Sparse Matrix-Matrix Multiplication on GPUs
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Ginkgo: A high performance numerical linear algebra library
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A Tensor-Based Approach to Dempster-Shafer Computing for Evidence Combination
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PERBANDINGAN ALGORITMA DJIKSTRA DAN ALGORITMA BIDIRECTIONAL DIJKSTRA DALAM PENCARIAN RUTE TERPENDEK
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Evaluating the Performance of NVIDIA's A100 Ampere GPU for Sparse Linear Algebra Computations
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