output
20182025
most citedTensorDash: Exploiting Sparsity to Accelerate Deep Neural Network Training and Inference

80 citations

researchers with a paper here
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Showing 2020Show all

2 papers · 1 filter

cs.AR2020★ 80 cited

TensorDash: Exploiting Sparsity to Accelerate Deep Neural Network Training and Inference

Mostafa Mahmoud, Isak Edo, Ali Hadi Zadeh +4

TensorDash is a hardware level technique for enabling data-parallel MAC units to take advantage of sparsity in their input operand streams. When used to compose a hardware accelera…

cs.CL2020★ 26 cited

How fine can fine-tuning be? Learning efficient language models

Evani Radiya-Dixit, Xin Wang

State-of-the-art performance on language understanding tasks is now achieved with increasingly large networks; the current record holder has billions of parameters. Given a languag…