Efficient and portable GEMM-based convolution operators for deep neural network training on multicore processors
Summary
Efficient and portable GEMM-based convolution operators for deep neural network training on multicore processors is a scholarly article[1].
Key Facts
Efficient and portable GEMM-based convolution operators for deep neural network training on multicore processors's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Efficient and portable GEMM-based convolution operators for deep neural network training on multicore processors. Retrieved May 24, 2026, from https://4ort.xyz/entity/efficient-and-portable-gemm-based-convolution-operators-for-deep-neural-network-training-on-multicore-processors
MLA“Efficient and portable GEMM-based convolution operators for deep neural network training on multicore processors.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/efficient-and-portable-gemm-based-convolution-operators-for-deep-neural-network-training-on-multicore-processors.
BibTeX@misc{4ortxyz_efficient-and-portable-gemm-based-convolution-operators-for-deep-neural-network-training-on-multicore-processors_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Efficient and portable GEMM-based convolution operators for deep neural network training on multicore processors}}, year = {2026}, url = {https://4ort.xyz/entity/efficient-and-portable-gemm-based-convolution-operators-for-deep-neural-network-training-on-multicore-processors}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Efficient and portable GEMM-based convolution operators for deep neural network training on multicore processors — https://4ort.xyz/entity/efficient-and-portable-gemm-based-convolution-operators-for-deep-neural-network-training-on-multicore-processors (retrieved 2026-05-24)
