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Mahdi Torabzadehkashi
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2020 – today
- 2022
- [j3]Ali Heydarigorji
, Siavash Rezaei
, Mahdi Torabzadehkashi
, Hossein Bobarshad
, Vladimir Castro Alves, Pai H. Chou:
Leveraging Computational Storage for Power-Efficient Distributed Data Analytics. ACM Trans. Embed. Comput. Syst. 21(6): 82:1-82:36 (2022) - [c6]Ali Heydarigorji, Mahdi Torabzadehkashi, Siavash Rezaei, Hossein Bobarshad, Vladimir Castro Alves, Pai H. Chou:
In-storage Processing of I/O Intensive Applications on Computational Storage Drives. ISQED 2022: 1-6 - 2021
- [i3]Ali Heydari Gorji, Mahdi Torabzadehkashi, Siavash Rezaei, Hossein Bobarshad, Vladimir Castro Alves, Pai H. Chou:
In-storage Processing of I/O Intensive Applications on Computational Storage Drives. CoRR abs/2112.12415 (2021) - 2020
- [j2]Jae Young Do, Victor da Cruz Ferreira, Hossein Bobarshad
, Mahdi Torabzadehkashi
, Siavash Rezaei, Ali Heydarigorji
, Diego Fonseca Pereira de Souza, Brunno F. Goldstein, Leandro Santiago
, Min Soo Kim, Priscila M. V. Lima, Felipe M. G. França
, Vladimir Castro Alves:
Cost-effective, Energy-efficient, and Scalable Storage Computing for Large-scale AI Applications. ACM Trans. Storage 16(4): 21:1-21:37 (2020) - [c5]Ali Heydari Gorji
, Mahdi Torabzadehkashi, Siavash Rezaei, Hossein Bobarshad, Vladimir Castro Alves, Pai H. Chou:
Stannis: Low-Power Acceleration of DNN Training Using Computational Storage Devices. DAC 2020: 1-6 - [c4]Ali Heydari Gorji, Siavash Rezaei, Mahdi Torabzadehkashi, Hossein Bobarshad, Vladimir Castro Alves, Pai H. Chou:
HyperTune: Dynamic Hyperparameter Tuning for Efficient Distribution of DNN Training Over Heterogeneous Systems. ICCAD 2020: 88:1-88:8 - [i2]Ali Heydarigorji, Mahdi Torabzadehkashi, Siavash Rezaei, Hossein Bobarshad, Vladimir Castro Alves, Pai H. Chou:
STANNIS: Low-Power Acceleration of Deep Neural Network Training Using Computational Storage. CoRR abs/2002.07215 (2020) - [i1]Ali Heydarigorji, Siavash Rezaei, Mahdi Torabzadehkashi, Hossein Bobarshad, Vladimir Castro Alves, Pai H. Chou:
HyperTune: Dynamic Hyperparameter Tuning For Efficient Distribution of DNN Training Over Heterogeneous Systems. CoRR abs/2007.08077 (2020)
2010 – 2019
- 2019
- [b1]Mahdi Torabzadehkashi:
SoC-Based In-Storage Processing: Bringing Flexibility and Efficiency to Near-Data Processing. University of California, Irvine, USA, 2019 - [j1]Mahdi Torabzadehkashi
, Siavash Rezaei, Ali Heydarigorji, Hossein Bobarshad, Vladimir Castro Alves, Nader Bagherzadeh
:
Computational storage: an efficient and scalable platform for big data and HPC applications. J. Big Data 6: 100 (2019) - [c3]Mahdi Torabzadehkashi
, Ali Heydarigorji, Siavash Rezaei, Hossein Bobarshad, Vladimir Castro Alves, Nader Bagherzadeh
:
Accelerating HPC Applications Using Computational Storage Devices. HPCC/SmartCity/DSS 2019: 1878-1885 - [c2]Mahdi Torabzadehkashi
, Siavash Rezaei, Ali Heydarigorji
, Hossein Bobarshad, Vladimir Castro Alves, Nader Bagherzadeh
:
Catalina: In-Storage Processing Acceleration for Scalable Big Data Analytics. PDP 2019: 430-437 - 2018
- [c1]Mahdi Torabzadehkashi
, Siavash Rezaei, Vladimir Castro Alves, Nader Bagherzadeh
:
CompStor: An In-storage Computation Platform for Scalable Distributed Processing. IPDPS Workshops 2018: 1260-1267
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