Malte J. Rasch

Joined

July 2019

Names

Malte J. Rasch

Emails

****@ibm.com (Confirmed)

****@gmail.com (Confirmed)

****@sony.com (Confirmed)

Personal Links

Google Scholar

DBLP

ORCID

Career & Education History

Principal Researcher

Sony Europe Ltd. (sony.com)

2024 – 2025

Researcher

International Business Machines (ibm.com)

2017 – 2023

Associate Professor

Beijing Normal University (bnu.edu.cn)

2013 – 2016

Postdoc

Institute of Neuroscience, Shanghai, China (ion.ac.cn)

2009 – 2012

PhD student

Sony AI , Technische Universität Graz (tugraz.at)

2004 – 2008

Advisors, Relations & Conflicts

No relations added

Expertise

AI for Chip Design

2024 – 2025

Neuromorphic AI hardware accelerator

2017 – 2023

Computational Neuroscience

2004 – 2023

Machine learning

2004 – 2023

Publications

Towards Exact Gradient-based Training on Analog In-memory Computing
Zhaoxian Wu, Tayfun Gokmen, Malte J. Rasch, Tianyi Chen
- NeurIPS 2024 poster
- Readers: Everyone
Multi-Function Multi-Way Analog Technology for Sustainable Machine Intelligence Computation
Vassilis Kalantzis, Mark S. Squillante, Shashanka Ubaru, Tayfun Gokmen, Chai Wah Wu, Anshul Gupta, Haim Avron, Tomasz Nowicki, Malte J. Rasch, O. Murat Onen, Vanessa López-Marrero, Effendi Leobandung, Yasuteru Kohda, Wilfried Haensch, Lior Horesh
- CoRR 2024
- Readers: Everyone
Improving the Accuracy of Analog-Based In-Memory Computing Accelerators Post-Training
Corey Lammie, Athanasios Vasilopoulos, Julian Büchel, Giacomo Camposampiero, Manuel Le Gallo, Malte J. Rasch, Abu Sebastian
- CoRR 2024
- Readers: Everyone
AnalogNAS: A Neural Network Design Framework for Accurate Inference with Analog In-Memory Computing
Hadjer Benmeziane, Corey Lammie, Irem Boybat, Malte J. Rasch, Manuel Le Gallo, Hsinyu Tsai, Ramachandran Muralidhar, Smaïl Niar, Hamza Ouarnoughi, Vijay Narayanan, Abu Sebastian, Kaoutar El Maghraoui
- CoRR 2023
- Readers: Everyone
Impact of Phase-Change Memory Drift on Energy Efficiency and Accuracy of Analog Compute-in-Memory Deep Learning Inference (Invited)
Martin M. Frank, Ning Li, Malte J. Rasch, Shubham Jain, Ching-Tzu Chen, Ramachandran Muralidhar, Jin-Ping Han, Vijay Narayanan, Timothy Philip, Kevin Brew, Andrew Simon, Iqbal Saraf, Nicole Saulnier, Irem Boybat, Stanislaw Wozniak, Abu Sebastian, Pritish Narayanan, Charles Mackin, An Chen, Hsinyu Tsai et al. (1 additional authors not shown)
- IRPS 2023
- Readers: Everyone
Using the IBM Analog In-Memory Hardware Acceleration Kit for Neural Network Training and Inference
Manuel Le Gallo, Corey Lammie, Julian Büchel, Fabio Carta, Omobayode Fagbohungbe, Charles Mackin, Hsinyu Tsai, Vijay Narayanan, Abu Sebastian, Kaoutar El Maghraoui, Malte J. Rasch
- CoRR 2023
- Readers: Everyone
Architectures and Circuits for Analog-memory-based Hardware Accelerators for Deep Neural Networks (Invited)
Hsinyu Tsai, Pritish Narayanan, Shubham Jain, Stefano Ambrogio, Kohji Hosokawa, Masatoshi Ishii, Charles Mackin, Ching-Tzu Chen, Atsuya Okazaki, Akiyo Nomura, Irem Boybat, Ramachandran Muralidhar, Martin M. Frank, Takeo Yasuda, Alexander M. Friz, Yasuteru Kohda, An Chen, Andrea Fasoli, Malte J. Rasch, Stanislaw Wozniak et al. (3 additional authors not shown)
- ISCAS 2023
- Readers: Everyone
Hardware-aware training for large-scale and diverse deep learning inference workloads using in-memory computing-based accelerators
Malte J. Rasch, Charles Mackin, Manuel Le Gallo, An Chen, Andrea Fasoli, Frédéric Odermatt, Ning Li, S. R. Nandakumar, Pritish Narayanan, Hsinyu Tsai, Geoffrey W. Burr, Abu Sebastian, Vijay Narayanan
- 2023 (modified: 17 Apr 2023)
- CoRR 2023
- Readers: Everyone
Fast offset corrected in-memory training
Malte J. Rasch, Fabio Carta, Omobayode Fagbohungbe, Tayfun Gokmen
- 2023 (modified: 17 Apr 2023)
- CoRR 2023
- Readers: Everyone

View all 32 publications

Co-Authors

View all 103 co-authors