A learning-based recommender system for autotuning design flows of industrial high-performance processors
- Jihye Kwon
- Matt Ziegler
- et al.
- 2019
- DAC 2019
Publications
This is our catalog of publications authored by IBM researchers, in collaboration with the global research community. It’s an ever-growing body of work that shows why IBM is one of the most important contributors to modern computing.
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8 results at DAC 2019
(Invited) cross-layer resilience: Challenges, insights, and the road ahead
- Eric Cheng
- Daniel Mueller-Gritschneder
- et al.
- 2019
- DAC 2019
NAPEL: Near-memory computing application performance prediction via ensemble learning
- Gagandeep Singh
- Juan Gomez-Luna
- et al.
- 2019
- DAC 2019
A memory-efficient markov decision process computation framework using BDD-based sampling representation
- He Zhou
- Sunil P. Khatri
- et al.
- 2019
- DAC 2019
FPGA/DNN co-design: An efficient design methodology for IoT intelligence on the edge
- Cong Hao
- Xiaofan Zhang
- et al.
- 2019
- DAC 2019
Comprehensive search for ECO rectification using symbolic sampling
- Victor N. Kravets
- Nian Ze Lee
- et al.
- 2019
- DAC 2019
BiScaled-DNN: Quantizing long-tailed datastructures with two scale factors for deep neural networks
- Shubham Jain
- Swagath Venkataramani
- et al.
- 2019
- DAC 2019
Efficient circuits for quantum search over 2D square lattice architecture
- Shaohan Hu
- Dmitri Maslov
- et al.
- 2019
- DAC 2019