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Optimizing SpMV for Diagonal Sparse Matrices on GPU
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Fast Sparse Matrix-Vector Multiplication by Exploiting Variable Block Structure
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Optimizing Sparse Matrix Computations for Register Reuse in SPARSITY
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When cache blocking of sparse matrix vector multiply works and why
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Optimization of sparse matrix-vector multiplication on emerging multicore platforms
inferredcites →https://doi.org/10.1016/j.pepi.2006.03.014openalex-snapshot
Modelling the core convection using finite element and finite difference methods
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OSKI: A library of automatically tuned sparse matrix kernels
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Optimal loop unrolling for GPGPU programs
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Iterative Methods for Sparse Linear Systems
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Accelerating sparse matrix computations via data compression
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Optimizing sparse matrix-vector multiplication using index and value compression
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Fast scan algorithms on graphics processors
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Pattern-based sparse matrix representation for memory-efficient SMVM kernels
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Implementing sparse matrix-vector multiplication on throughput-oriented processors
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Streamlining GPU applications on the fly
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Performance Optimizations and Bounds for Sparse Matrix-Vector Multiply
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/cpe.3217openalex-snapshot
Accurate cross‒architecture performance modeling for sparse matrix‒vector multiplication (SpMV) on GPUs
inferred← citeshttps://doi.org/10.1002/cpe.6230openalex-snapshot
A new diagonal storage for efficient implementation of sparse matrix–vector multiplication on graphics processing unit
inferred← citeshttps://doi.org/10.1007/978-3-031-40942-4_2openalex-snapshot
Towards Reducing Communications in Sparse Matrix Kernels
inferred← citeshttps://doi.org/10.1007/978-981-13-5910-1_7openalex-snapshot
A Parallel Solving Algorithm on GPU for the Time-Domain Linear System with Diagonal Sparse Matrices
inferred← citeshttps://doi.org/10.1007/978-981-97-0801-7_18openalex-snapshot
MANet: An Architecture Adaptive Method for Sparse Matrix Format Selection
inferred← citeshttps://doi.org/10.1007/s00607-016-0534-5openalex-snapshot
Energy prediction of CUDA application instances using dynamic regression models
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A CUDA based parallel multi-phase oil reservoir simulator
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Adaptive diagonal sparse matrix-vector multiplication on GPU
inferred← citeshttps://doi.org/10.1109/hpca61900.2025.00068openalex-snapshot
A Hardware-Software Design Framework for SpMV Acceleration with Flexible Access Pattern Portfolio
inferred← citeshttps://doi.org/10.1109/hpec.2016.7761634openalex-snapshot
How naive is naive SpMV on the GPU?
inferred← citeshttps://doi.org/10.1109/ipdps.2015.100openalex-snapshot
Reducing Vector I/O for Faster GPU Sparse Matrix-Vector Multiplication
inferred← citeshttps://doi.org/10.1109/ipdpsw63119.2024.00012openalex-snapshot
Towards Dynamic Autotuning of SpMV in CUSP Library
inferred← citeshttps://doi.org/10.1109/itca52113.2020.00081openalex-snapshot
Research on Performance Optimization for Sparse Matrix-Vector Multiplication in Multi/Many-core Architecture
inferred← citeshttps://doi.org/10.1109/nas.2012.11openalex-snapshot
Parallel Sparse Matrix Multiplication for Preconditioning and SSTA on a Many-Core Architecture
inferred← citeshttps://doi.org/10.1109/tpds.2022.3170501openalex-snapshot
TaiChi: A Hybrid Compression Format for Binary Sparse Matrix-Vector Multiplication on GPU
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Autotuning Runtime Specialization for Sparse Matrix-Vector Multiplication
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Energy and Performance Prediction of CUDA Applications using Dynamic Regression Models
inferred← citeshttps://doi.org/10.1145/3017994openalex-snapshot
Sparse Matrix-Vector Multiplication on GPGPUs
inferred← citeshttps://doi.org/10.1145/3079079.3079086openalex-snapshot
Globally homogeneous, locally adaptive sparse matrix-vector multiplication on the GPU
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Adaptive sparse tiling for sparse matrix multiplication
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Optimizing the linear fascicle evaluation algorithm for many-core systems
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Optimizing the Linear Fascicle Evaluation Algorithm for Multi-core and Many-core Systems
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Optimization Techniques for GPU Programming
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A hybrid format for better performance of sparse matrix-vector multiplication on a GPU
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Accelerating irregular applications via efficient synchronization and data access techniques
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Leveraging index compression techniques to optimize the use of co-processors
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A Review of Parallel Optimization Techniques of Solving Ultra-Large-Scale Sparse Linear Equations
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Optimized GPU algorithms for sparse data problems
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