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Analytical Modeling Is Enough for High-Performance BLIS

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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/s11227-014-1098-9openalex-snapshot

A Matrix–Matrix Multiplication methodology for single/multi-core architectures using SIMD

inferredcites →https://doi.org/10.1016/s0167-8191(00)00086-7openalex-snapshot

New trends in high performance computing

inferredcites →https://doi.org/10.1016/s0167-8191(00)00087-9openalex-snapshot

Automated empirical optimizations of software and the ATLAS project

inferredcites →https://doi.org/10.1109/ipdps.2014.110openalex-snapshot

Anatomy of High-Performance Many-Threaded Matrix Multiplication

inferredcites →https://doi.org/10.1109/jproc.2004.840444openalex-snapshot

Is Search Really Necessary to Generate High-Performance BLAS?

inferredcites →https://doi.org/10.1109/sbac-pad.2012.35openalex-snapshot

On the Efficiency of Register File versus Broadcast Interconnect for Collective Communications in Data-Parallel Hardware Accelerators

inferredcites →https://doi.org/10.1109/tc.2012.132openalex-snapshot

Codesign Tradeoffs for High-Performance, Low-Power Linear Algebra Architectures

inferredcites →https://doi.org/10.1145/1188455openalex-snapshot

Proceedings of the 2006 ACM/IEEE conference on Supercomputing - SC '06

inferredcites →https://doi.org/10.1145/1356052.1356053openalex-snapshot

Anatomy of high-performance matrix multiplication

inferredcites →https://doi.org/10.1145/1377603.1377607openalex-snapshot

High-performance implementation of the level-3 BLAS

inferredcites →https://doi.org/10.1145/2503210.2503219openalex-snapshot

AUGEM

inferredcites →https://doi.org/10.1145/2591635.2667174openalex-snapshot

Optimizing matrix multiply using PHiPAC

inferredcites →https://doi.org/10.1145/263580.263662openalex-snapshot

Optimizing matrix multiply using PHiPAC

inferredcites →https://doi.org/10.1145/2755561openalex-snapshot

The BLIS Framework

inferredcites →https://doi.org/10.1145/2764454openalex-snapshot

BLIS: A Framework for Rapidly Instantiating BLAS Functionality

inferredcites →https://doi.org/10.1145/355841.355847openalex-snapshot

Basic Linear Algebra Subprograms for Fortran Usage

inferredcites →https://doi.org/10.1145/42288.42291openalex-snapshot

An extended set of FORTRAN basic linear algebra subprograms

inferredcites →https://doi.org/10.1145/77626.79170openalex-snapshot

A set of level 3 basic linear algebra subprograms

inferredcites →https://doi.org/10.5555/509058.509096openalex-snapshot

Automatically Tuned Linear Algebra Software

What points at this work

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

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Analytical modeling of matrix–vector multiplication on multicore processors

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Fast matrix multiplication via compiler‐only layered data reorganization and intrinsic lowering

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Automatic Memory-Efficient Scheduling of CNNs

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inferred← citeshttps://doi.org/10.1007/978-3-031-30445-3_20openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/978-3-031-33159-6_17openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/978-3-031-35995-8_47openalex-snapshot

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inferred← citeshttps://doi.org/10.1007/978-3-031-47859-8_12openalex-snapshot

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Time and energy modeling of a high-performance multi-threaded Cholesky factorization

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Auto-tuning GEMM kernels on the Intel KNL and Intel Skylake-SP processors

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Low precision matrix multiplication for efficient deep learning in NVIDIA Carmel processors

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A BLIS-like matrix multiplication for machine learning in the RISC-V ISA-based GAP8 processor

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inferred← citeshttps://doi.org/10.1063/5.0081426openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/bigdata.2018.8622013openalex-snapshot

A Flexible-blocking Based Approach for Performance Tuning of Matrix Multiplication Routines for Large Matrices with Edge Cases

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oneDNN Graph Compiler: A Hybrid Approach for High-Performance Deep Learning Compilation

inferred← citeshttps://doi.org/10.1109/cgo57630.2024.10444883openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/hpca56546.2023.10071018openalex-snapshot

Chimera: An Analytical Optimizing Framework for Effective Compute-intensive Operators Fusion

inferred← citeshttps://doi.org/10.1109/hpca56546.2023.10071076openalex-snapshot

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High-Performance Matrix Multiplication on the New Generation Shenwei Processor

inferred← citeshttps://doi.org/10.1109/hpec.2017.8091024openalex-snapshot

Mixed data layout kernels for vectorized complex arithmetic

inferred← citeshttps://doi.org/10.1109/hpec55821.2022.9926408openalex-snapshot

Im2win: Memory Efficient Convolution On SIMD Architectures

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Generating Families of Practical Fast Matrix Multiplication Algorithms

inferred← citeshttps://doi.org/10.1109/ipdps49936.2021.00019openalex-snapshot

Characterizing Small-Scale Matrix Multiplications on ARMv8-based Many-Core Architectures

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inferred← citeshttps://doi.org/10.1109/ipdps65963.2026.00102openalex-snapshot

Demystifying ARM SME to Optimize General Matrix Multiplications

inferred← citeshttps://doi.org/10.1109/ipdpsw.2016.104openalex-snapshot

Refactoring Conventional Task Schedulers to Exploit Asymmetric ARM big.LITTLE Architectures in Dense Linear Algebra

inferred← citeshttps://doi.org/10.1109/ipdpsw.2018.00064openalex-snapshot

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Latency-Critical Quantized Inference With Transformer Decoders on ARM and RISC-V CPUs

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inferred← citeshttps://doi.org/10.1109/pdp55904.2022.00023openalex-snapshot

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inferred← citeshttps://doi.org/10.1145/3595178openalex-snapshot

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inferred← citeshttps://doi.org/10.31390/gradschool_dissertations.4486openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/electronics7120359openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/en15207509openalex-snapshot

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inferred← citeshttps://doi.org/10.48550/arxiv.1609.00076openalex-snapshot

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inferred← citeshttps://doi.org/10.48550/arxiv.1611.08035openalex-snapshot

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inferred← citeshttps://doi.org/10.48550/arxiv.1903.05575openalex-snapshot

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inferred← citeshttps://doi.org/10.48550/arxiv.1904.05717openalex-snapshot

The MOMMS Family of Matrix Multiplication Algorithms

inferred← citeshttps://doi.org/10.48550/arxiv.2003.00532openalex-snapshot

High Performance Code Generation in MLIR: An Early Case Study with GEMM

inferred← citeshttps://doi.org/10.48550/arxiv.2005.06410openalex-snapshot

High Performance and Portable Convolution Operators for ARM-based Multicore Processors

inferred← citeshttps://doi.org/10.48550/arxiv.2010.08040openalex-snapshot

Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization

inferred← citeshttps://doi.org/10.48550/arxiv.2104.13242openalex-snapshot

Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization (extended version)

inferred← citeshttps://doi.org/10.48550/arxiv.2104.14641openalex-snapshot

Tuna: A Static Analysis Approach to Optimizing Deep Neural Networks

inferred← citeshttps://doi.org/10.48550/arxiv.2105.09187openalex-snapshot

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inferred← citeshttps://doi.org/10.48550/arxiv.2108.02025openalex-snapshot

High-Performance Level-1 and Level-2 BLAS

inferred← citeshttps://doi.org/10.5555/3049832.3049846openalex-snapshot

Automatic generation of fast BLAS3-GEMM: a portable compiler approach

inferred← citeshttps://doi.org/10.5821/dissertation-2117-404668openalex-snapshot

Efficient hardware acceleration of deep neural networks via arithmetic complexity reduction

inferred← citeshttps://doi.org/10.6035/14101.2018.209077openalex-snapshot

Multithreaded Dense Linear Algebra on Asymmetric Multi-core Processors

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