From post

Accelerated Deep Learning for the Edge-to-Cloud continuum: a Specialized Full Stack derived from Algorithms.

. Georgia Institute of Technology, Atlanta, GA, USA, (2019)base-search.net (ftgeorgiatech:oai:smartech.gatech.edu:1853/61267).

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

 

Другие публикации лиц с тем же именем

Neural acceleration for GPU throughput processors., , , , и . MICRO, стр. 482-493. ACM, (2015)TABLA: A unified template-based framework for accelerating statistical machine learning., , , , , , и . HPCA, стр. 14-26. IEEE Computer Society, (2016)From high-level deep neural models to FPGAs., , , , , , , и . MICRO, стр. 17:1-17:12. IEEE Computer Society, (2016)The impact of 3D stacking on GPU-accelerated deep neural networks: An experimental study., , , , и . 3DIC, стр. 1-4. IEEE, (2016)Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Network., , , , , , и . ISCA, стр. 764-775. IEEE Computer Society, (2018)DACAPO: Accelerating Continuous Learning in Autonomous Systems for Video Analytics., , , , , , , , и . ISCA, стр. 1246-1261. IEEE, (2024)Domain-Specific Computational Storage for Serverless Computing., , , , , , , , , и 1 other автор(ы). CoRR, (2023)In-Storage Domain-Specific Acceleration for Serverless Computing., , , , , , , , , и 1 other автор(ы). ASPLOS (2), стр. 530-548. ACM, (2024)Accelerated Deep Learning for the Edge-to-Cloud continuum: a Specialized Full Stack derived from Algorithms.. Georgia Institute of Technology, Atlanta, GA, USA, (2019)base-search.net (ftgeorgiatech:oai:smartech.gatech.edu:1853/61267).Mixed-Signal Charge-Domain Acceleration of Deep Neural Networks through Interleaved Bit-Partitioned Arithmetic., , , , , , , и . PACT, стр. 399-411. ACM, (2020)