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Physically Accurate Learning-based Performance Prediction of Hardware-accelerated ML Algorithms.

H. Esmaeilzadeh, S. Ghodrati, A. Kahng, J. Kim, S. Kinzer, S. Kundu, R. Mahapatra, S. Manasi, S. Sapatnekar, Z. Wang, and Z. Zeng. MLCAD, page 119-126. ACM / IEEE, (2022)

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Joon-Young Kim

Nam-Joon Kim

Man Joon Kim

Joon-Soon Kim

Hyun-Joon Kim

Other publications of authors with the same name

TABLA: A unified template-based framework for accelerating statistical machine learning.D. Mahajan, J. Park, E. Amaro, H. Sharma, A. Yazdanbakhsh, J. Kim, and H. Esmaeilzadeh. HPCA, page 14-26. IEEE Computer Society, (2016)From high-level deep neural models to FPGAs.H. Sharma, J. Park, D. Mahajan, E. Amaro, J. Kim, C. Shao, A. Mishra, and H. Esmaeilzadeh. MICRO, page 17:1-17:12. IEEE Computer Society, (2016)Yin-Yang: Programming Abstractions for Cross-Domain Multi-Acceleration.J. Kim, B. Ahn, S. Kinzer, S. Ghodrati, R. Mahapatra, B. Yatham, S. Wang, D. Kim, P. Sarikhani, B. Mahmoudi and 3 other author(s). IEEE Micro, 42 (5): 89-98 (2022)In-RDBMS Hardware Acceleration of Advanced Analytics.D. Mahajan, J. Kim, J. Sacks, A. Ardalan, A. Kumar, and H. Esmaeilzadeh. Proc. VLDB Endow., 11 (11): 1317-1331 (2018)Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks.H. Sharma, J. Park, N. Suda, L. Lai, B. Chau, J. Kim, V. Chandra, and H. Esmaeilzadeh. CoRR, (2017)A Computational Stack for Cross-Domain Acceleration.S. Kinzer, J. Kim, S. Ghodrati, B. Yatham, A. Althoff, D. Mahajan, S. Lerner, and H. Esmaeilzadeh. HPCA, page 54-70. IEEE, (2021)VeriGOOD-ML: An Open-Source Flow for Automated ML Hardware Synthesis.H. Esmaeilzadeh, S. Ghodrati, J. Gu, S. Guo, A. Kahng, J. Kim, S. Kinzer, R. Mahapatra, S. Manasi, E. Mascarenhas and 6 other author(s). ICCAD, page 1-7. IEEE, (2021)An Open-Source ML-Based Full-Stack Optimization Framework for Machine Learning Accelerators.H. Esmaeilzadeh, S. Ghodrati, A. Kahng, J. Kim, S. Kinzer, S. Kundu, R. Mahapatra, S. Manasi, S. Sapatnekar, Z. Wang and 1 other author(s). CoRR, (2023)Physically Accurate Learning-based Performance Prediction of Hardware-accelerated ML Algorithms.H. Esmaeilzadeh, S. Ghodrati, A. Kahng, J. Kim, S. Kinzer, S. Kundu, R. Mahapatra, S. Manasi, S. Sapatnekar, Z. Wang and 1 other author(s). MLCAD, page 119-126. ACM / IEEE, (2022)Scale-out acceleration for machine learning.J. Park, H. Sharma, D. Mahajan, J. Kim, P. Olds, and H. Esmaeilzadeh. MICRO, page 367-381. ACM, (2017)

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Disambiguation of "Kim, Joon Kyung"

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Physically Accurate Learning-based Performance Prediction of Hardware-accelerated ML Algorithms.

Please choose a person to relate this publication to

Joon-Young Kim

Nam-Joon Kim

Man Joon Kim

Joon-Soon Kim

Hyun-Joon Kim

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Kim, Joon Kyung"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Physically Accurate Learning-based Performance Prediction of Hardware-accelerated ML Algorithms.

Please choose a person to relate this publication to

Joon-Young Kim

Nam-Joon Kim

Man Joon Kim

Joon-Soon Kim

Hyun-Joon Kim

Other publications of authors with the same name

Disambiguation

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URL
DOI
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Physically Accurate Learning-based Performance Prediction of Hardware-accelerated ML Algorithms.