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YaConv: Convolution with Low Cache Footprint

https://doi.org/10.1145/3570305
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What this work says

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

inferredcites →https://doi.org/10.1016/s0898-1221(96)90463-0openalex-snapshot
Advances in neural information processing systems 7
inferredcites →https://doi.org/10.1109/cgo51591.2021.9370308openalex-snapshot
MLIR: Scaling Compiler Infrastructure for Domain Specific Computation
inferredcites →https://doi.org/10.1109/cvpr.2016.435openalex-snapshot
Fast Algorithms for Convolutional Neural Networks
inferredcites →https://doi.org/10.1109/icpads.2012.97openalex-snapshot
Model-driven Level 3 BLAS Performance Optimization on Loongson 3A Processor
inferredcites →https://doi.org/10.1109/ipdps.2014.110openalex-snapshot
Anatomy of High-Performance Many-Threaded Matrix Multiplication
inferredcites →https://doi.org/10.1109/ipdps47924.2020.00032openalex-snapshot
Harnessing Deep Learning via a Single Building Block
inferredcites →https://doi.org/10.1109/ipdpsw50202.2020.00154openalex-snapshot
Indirect Deconvolution Algorithm
inferredcites →https://doi.org/10.1109/sbac-pad49847.2020.00023openalex-snapshot
High Performance and Portable Convolution Operators for Multicore Processors
inferredcites →https://doi.org/10.1109/sbac-pad49847.2020.00024openalex-snapshot
High-Performance Low-Memory Lowering: GEMM-based Algorithms for DNN Convolution
inferredcites →https://doi.org/10.1109/sc.2018.00069openalex-snapshot
Anatomy of High-Performance Deep Learning Convolutions on SIMD Architectures
inferredcites →https://doi.org/10.1145/1356052.1356053openalex-snapshot
Anatomy of high-performance matrix multiplication
inferredcites →https://doi.org/10.1145/2925987openalex-snapshot
Analytical Modeling Is Enough for High-Performance BLIS
inferredcites →https://doi.org/10.1145/3177885openalex-snapshot
Optimizing Convolutional Neural Networks on the Sunway TaihuLight Supercomputer
inferredcites →https://doi.org/10.1145/3433103openalex-snapshot
PolyDL
inferredcites →https://doi.org/10.1145/3445814.3446759openalex-snapshot
Analytical characterization and design space exploration for optimization of CNNs
inferredcites →https://doi.org/10.1145/3532863openalex-snapshot
An Accelerator for Sparse Convolutional Neural Networks Leveraging Systolic General Matrix-matrix Multiplication
inferredcites →https://doi.org/10.1201/9781315141312-9openalex-snapshot
Convolution Algorithms
inferredcites →https://doi.org/10.48550/arxiv.2006.06762openalex-snapshot
Ansor: Generating High-Performance Tensor Programs for Deep Learning

What points at this work

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

inferred← citeshttps://doi.org/10.1007/s11227-025-07706-9openalex-snapshot
Batched data layout optimization for Im2col-based convolutions on CPUs
inferred← citeshttps://doi.org/10.1016/j.future.2026.108866openalex-snapshot
Optimizing convolution operator execution flow in eager mode on Ascend 910B
inferred← citeshttps://doi.org/10.1016/j.jpdc.2024.104869openalex-snapshot
Dataflow optimization with layer-wise design variables estimation method for enflame CNN accelerators
inferred← citeshttps://doi.org/10.1016/j.parco.2025.103137openalex-snapshot
Multi-level parallelism optimization for two-dimensional convolution vectorization method on multi-core vector accelerator
inferred← citeshttps://doi.org/10.1109/asp-dac58780.2024.10473863openalex-snapshot
Quantization-aware Optimization Approach for CNNs Inference on CPUs
inferred← citeshttps://doi.org/10.1109/jiot.2025.3613691openalex-snapshot
A Survey of AI Inference Technologies for On-Device Systems
inferred← citeshttps://doi.org/10.1109/tc.2025.3543677openalex-snapshot
nDirect2: A High-Performance Library for Direct Convolutions on Multicore CPUs
inferred← citeshttps://doi.org/10.1145/3625004openalex-snapshot
Advancing Direct Convolution Using Convolution Slicing Optimization and ISA Extensions
inferred← citeshttps://doi.org/10.1145/3754598.3754619openalex-snapshot
Optimizing Direct Convolutions on High-Performance Multi-Core DSPs
inferred← citeshttps://doi.org/10.47749/t/unicamp.2023.1376865openalex-snapshot
Improving direct convolution through tensor slicing, vectorized packing and ISA extensions
inferred← citeshttps://doi.org/10.5753/ctd.2024.2901openalex-snapshot
Improving Direct Convolution through Tensor Slicing, Vectorized Packing and ISA Extensions
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