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Hiddenite: 4K-PE Hidden Network Inference 4D-Tensor Engine Exploiting On-Chip Model Construction Achieving 34.8-to-16.0TOPS/W for CIFAR-100 and ImageNet
Research article (2022 IEEE International Solid- State Circuits Conference (ISSCC), 2022) · cited 21× · AI/ML
Hiddenite: 4K-PE Hidden Network Inference 4D-Tensor Engine Exploiting On-Chip Model Construction Achieving 34.8-to-16.0TOPS/W for CIFAR-100 and ImageNet
Summary
Hiddenite: 4K-PE Hidden Network Inference 4D-Tensor Engine Exploiting On-Chip Model Construction Achieving 34.8-to-16.0TOPS/W for CIFAR-100 and ImageNet is a scholarly article[1].
Key Facts
Hiddenite: 4K-PE Hidden Network Inference 4D-Tensor Engine Exploiting On-Chip Model Construction Achieving 34.8-to-16.0TOPS/W for CIFAR-100 and ImageNet's instance of is recorded as scholarly article[2].
References
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APA4ort.xyz Knowledge Graph. (2026). Hiddenite: 4K-PE Hidden Network Inference 4D-Tensor Engine Exploiting On-Chip Model Construction Achieving 34.8-to-16.0TOPS/W for CIFAR-100 and ImageNet. Retrieved May 24, 2026, from https://4ort.xyz/entity/hiddenite-4k-pe-hidden-network-inference-4d-tensor-engine-exploiting-on-chip-model-construction-achieving-34-8-to-16-0to
MLA“Hiddenite: 4K-PE Hidden Network Inference 4D-Tensor Engine Exploiting On-Chip Model Construction Achieving 34.8-to-16.0TOPS/W for CIFAR-100 and ImageNet.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/hiddenite-4k-pe-hidden-network-inference-4d-tensor-engine-exploiting-on-chip-model-construction-achieving-34-8-to-16-0to.
BibTeX@misc{4ortxyz_hiddenite-4k-pe-hidden-network-inference-4d-tensor-engine-exploiting-on-chip-model-construction-achieving-34-8-to-16-0to_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Hiddenite: 4K-PE Hidden Network Inference 4D-Tensor Engine Exploiting On-Chip Model Construction Achieving 34.8-to-16.0TOPS/W for CIFAR-100 and ImageNet}}, year = {2026}, url = {https://4ort.xyz/entity/hiddenite-4k-pe-hidden-network-inference-4d-tensor-engine-exploiting-on-chip-model-construction-achieving-34-8-to-16-0to}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Hiddenite: 4K-PE Hidden Network Inference 4D-Tensor Engine Exploiting On-Chip Model Construction Achieving 34.8-to-16.0TOPS/W for CIFAR-100 and ImageNet — https://4ort.xyz/entity/hiddenite-4k-pe-hidden-network-inference-4d-tensor-engine-exploiting-on-chip-model-construction-achieving-34-8-to-16-0to (retrieved 2026-05-24)
