On the public citation graph

Using Ginkgo's memory accessor for improving the accuracy of memory‐bound low precision BLAS

https://doi.org/10.1002/spe.3041
0 signed · 42 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

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

inferredcites →https://doi.org/10.1002/cpe.1164openalex-snapshot
Implementation of mixed precision in solving systems of linear equations on the Cell processor
inferredcites →https://doi.org/10.1007/978-3-319-63390-9_2openalex-snapshot
Ascertaining Uncertainty for Efficient Exact Cache Analysis
inferredcites →https://doi.org/10.1016/j.parco.2008.12.006openalex-snapshot
Optimization of sparse matrix-vector multiplication on emerging multicore platforms
inferredcites →https://doi.org/10.1017/s0962492916000015openalex-snapshot
Linear algebra software for large-scale accelerated multicore computing
inferredcites →https://doi.org/10.1109/iiswc.2014.6983061openalex-snapshot
Extending the roofline model: Bottleneck analysis with microarchitectural constraints
inferredcites →https://doi.org/10.1109/ipdps.2016.11openalex-snapshot
Fast Error-Bounded Lossy HPC Data Compression with SZ
inferredcites →https://doi.org/10.1109/ipdps.2017.115openalex-snapshot
Significantly Improving Lossy Compression for Scientific Data Sets Based on Multidimensional Prediction and Error-Controlled Quantization
inferredcites →https://doi.org/10.1109/ipdpsw.2018.00091openalex-snapshot
NVIDIA Tensor Core Programmability, Performance & Precision
inferredcites →https://doi.org/10.1109/ispass.2011.5762713openalex-snapshot
Evaluation and optimization of multicore performance bottlenecks in supercomputing applications
inferredcites →https://doi.org/10.1109/ispass.2014.6844463openalex-snapshot
Applying the roofline model
inferredcites →https://doi.org/10.1109/l-ca.2013.6openalex-snapshot
Cache-aware Roofline model: Upgrading the loft
inferredcites →https://doi.org/10.1109/tit.2014.2314676openalex-snapshot
Lossy Compression via Sparse Linear Regression: Computationally Efficient Encoding and Decoding
inferredcites →https://doi.org/10.1109/tpds.2019.2894404openalex-snapshot
Optimizing Lossy Compression Rate-Distortion from Automatic Online Selection between SZ and ZFP
inferredcites →https://doi.org/10.1109/tvcg.2006.143openalex-snapshot
Fast and Efficient Compression of Floating-Point Data
inferredcites →https://doi.org/10.1109/tvcg.2014.2346458openalex-snapshot
Fixed-Rate Compressed Floating-Point Arrays
inferredcites →https://doi.org/10.1137/0907058openalex-snapshot
GMRES: A Generalized Minimal Residual Algorithm for Solving Nonsymmetric Linear Systems
inferredcites →https://doi.org/10.1137/1.9780898718003openalex-snapshot
Iterative Methods for Sparse Linear Systems
inferredcites →https://doi.org/10.1137/1.9780898718027openalex-snapshot
Accuracy and Stability of Numerical Algorithms
inferredcites →https://doi.org/10.1137/12088358xopenalex-snapshot
A Fast Dense Triangular Solve in CUDA
inferredcites →https://doi.org/10.1145/1498765.1498785openalex-snapshot
Roofline
inferredcites →https://doi.org/10.1145/216585.216588openalex-snapshot
Hitting the memory wall
inferredcites →https://doi.org/10.1145/3380930openalex-snapshot
Load-balancing Sparse Matrix Vector Product Kernels on GPUs
inferredcites →https://doi.org/10.1145/3380934openalex-snapshot
Acceleration of PageRank with Customized Precision Based on Mantissa Segmentation
inferredcites →https://doi.org/10.1145/3480935openalex-snapshot
Ginkgo : A Modern Linear Operator Algebra Framework for High Performance Computing
inferredcites →https://doi.org/10.1145/567806.567807openalex-snapshot
An updated set of basic linear algebra subprograms (BLAS)
inferredcites →https://doi.org/10.1177/1094342010391989openalex-snapshot
The International Exascale Software Project roadmap
inferredcites →https://doi.org/10.1177/1094342018762036openalex-snapshot
Exploring the feasibility of lossy compression for PDE simulations
inferredcites →https://doi.org/10.1177/1094342019846547openalex-snapshot
Toward a modular precision ecosystem for high-performance computing
inferredcites →https://doi.org/10.21105/joss.02260openalex-snapshot
Ginkgo: A high performance numerical linear algebra library

What points at this work

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

inferred← citeshttps://doi.org/10.1002/spe.3155openalex-snapshot
Special issue on new trends in high‐performance computing: Software systems and applications
inferred← citeshttps://doi.org/10.1007/978-3-031-32041-5_9openalex-snapshot
A Mixed Precision Randomized Preconditioner for the LSQR Solver on GPUs
inferred← citeshttps://doi.org/10.1007/978-3-031-69583-4_2openalex-snapshot
Reduced-Precision and Reduced-Exponent Formats for Accelerating Adaptive Precision Sparse Matrix–Vector Product
inferred← citeshttps://doi.org/10.1016/j.future.2024.05.022openalex-snapshot
Multifacets of lossy compression for scientific data in the Joint-Laboratory of Extreme Scale Computing
inferred← citeshttps://doi.org/10.1017/s0962492922000022openalex-snapshot
Mixed precision algorithms in numerical linear algebra
inferred← citeshttps://doi.org/10.1109/mcsoc60832.2023.00094openalex-snapshot
Sparse Matrix-Vector Multiplication with Reduced-Precision Memory Accessor
inferred← citeshttps://doi.org/10.1109/scw63240.2024.00038openalex-snapshot
FRSZ2 for In-Register Block Compression Inside GMRES on GPUs
inferred← citeshttps://doi.org/10.1137/22m1522619openalex-snapshot
Adaptive Precision Sparse Matrix–Vector Product and Its Application to Krylov Solvers
inferred← citeshttps://doi.org/10.1145/3779120openalex-snapshot
Kernel Float: Unlocking Mixed-Precision GPU Programming
inferred← citeshttps://doi.org/10.1177/10943420221115140openalex-snapshot
Compressed basis GMRES on high-performance graphics processing units
inferred← citeshttps://doi.org/10.1177/10943420251392963openalex-snapshot
Performance evaluation of mixed-precision Runge–Kutta methods for the solution of partial differential equations
inferred← citeshttps://doi.org/10.70675/637bbb4az8197z400czbb8azdd0033abd8c4openalex-snapshot
Using Block Low-Rank compression in mixed precision for sparse direct linear solvers
inferred← citeshttps://doi.org/10.70675/82d78149z919cz4559z92e6z4f6a5508bb52openalex-snapshot
Mixed precision for High Performance Computing, application to low energy gamma radiation measurements
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.