TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning | Paper Citation Record

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Unresolved cited work

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Unresolved cited work

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Unresolved cited work

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Unresolved cited work

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This paper cites Competitive Analysis System for Theatrical Movie Releases Based on Movie Trailer Deep Video Representation.

TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Competitive Analysis System for Theatrical Movie Releases Based on Movie Trailer Deep Video Representation

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Unresolved cited work

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This paper cites Emer, and Vivienne Sze.

TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Emer, and Vivienne Sze

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This paper cites Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs.

TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs

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This paper cites Bit-Tactical: Exploiting Ineffectual Computations in Convolutional Neural Networks: Which, Why, and How.

TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Bit-Tactical: Exploiting Ineffectual Computations in Convolutional Neural Networks: Which, Why, and How

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Unresolved cited work

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This paper cites Lee, An- drey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, and Xuan Zhang.

TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Lee, An- drey Malevich, Dheevatsa Mudigere, Mikhail Smelyanskiy, Liang Xiong, and Xuan Zhang

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning One weird trick for parallelizing convolutional neural networks

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Unresolved cited work

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Reinhardt, and Thomas F

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Unresolved cited work

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Meaney, Lawrence D

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Moss, Srivatsan Krishnan, Eriko Nurvitadhi, Piotr Ratuszniak, Chris Johnson, Jaewoong Sim, Asit Mishra, Debbie Marr, Suchit Subhaschandra, and Philip H.W

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Moss, Eriko Nurvitadhi, Jaewoong Sim, Asit Mishra, Debbie Marr, Suchit Subhaschandra, and Philip H.W

Reference 51

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Unresolved cited work

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Keckler, and William J

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Reference 73

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Reference 75

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Reference 76

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Ramadge, Eric Nestler, and Naveen Verma

Reference 77

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Reference 78

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Whatmough, Sae Kyu Lee, Hyunkwang Lee, Saketh Rama, David Brooks, and Gu-Yeon Wei

Reference 79

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TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning Whatmough, Sae Kyu Lee, Niamh Mulholland, Patrick Hansen, Sreela Kodali, David C

Reference 80

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Observation 33c4a1bc-21ac-4aec-8c93-1251ee7c6ebb · outbound

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Reference 81

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This paper cites In Proceedings of the International Symposium on Microarchitecture (MICRO).

TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning In Proceedings of the International Symposium on Microarchitecture (MICRO)

Reference 2016

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