GCA'23
The 8th International Workshop on GPU Computing and AI
To be held in conjunction with CANDAR'23.
Built for massive parallelism, General Purpose computing on Graphics Processing Unit (GPGPU) has superseded high-performance CPU in several important tasks, including computer graphics, physics calculations, encryption/decryption and scientific computations. Also, GPGPUs have been considered as a natural alternative to fulfill the computing needs for Artificial Intelligence and Machine Learning applications. Recent developments have shown intensive research activity in these fields.
The goal of this workshop is to provide a forum to discuss and evaluate emerging techniques, platforms and applications, capable of harvesting the power of current GPGPUs as well as to share new ideas from the research area of Artificial Intelligence. (The topic of this workshop is not only “Both GPU and AI”, but also “Either GPU or AI.”)
The GCA workshop seeks for high-quality papers on various topics, including but not limited to:
- GPU computing
- GPU applications
- Computer graphics on GPUs
- GPU compilation
- GPU programming environments
- GPU power efficiency
- GPU architectures
- GPU theoretical computing models
- GPU benchmarking/measurements
- GPU embedded systems
- Multi-GPU systems
- GPU cluster
- Heterogeneous GPU platforms
- CPU-GPU cooperation
- CUDA/OpenCL/OpenACC
- Deep learning on GPUs
- Artificial intelligence
- Artificial neural networks
- Big data analytics
- Data mining
- Deep learning
- Experts systems
- Fuzzy logic
- Machine learning
- Natural language processing
- Computer vision
- Reinforcement learning
Paper format
- Regular paper: 5–7 pages
- Poster paper: 3–4 pages
Organizers
Workshop co-chairs
- Jacir L. Bordim (University of Brasilia)
- Yasuaki Ito (Hiroshima University)
Program Committee
- Ulisses Rodrigues Afonseca (Federal Institute of Goiás-Brazil)
- Eduardo Adilio Pelinson Alchieri (University of Brasília)
- Hidetoshi Ando (University of Yamanashi)
- Wei Der Chien (KTH Royal Institute of Technology)
- Tingxing Dong (Radeon Technologies Group, AMD.)
- Toshio Endo (Tokyo Institute of Technology)
- Marcos Fagundes Caetano (University of Brasília)
- Ken-ichi Fukui (Osaka University)
- Jing Gong (KTH Royal Institute of Technology)
- Kohei Hatano (Kyushu University)
- Takumi Honda (Fujitsu Limited)
- Tsutomu Inamoto (Ehime University)
- Humayun Kabir (Microsoft)
- Krzysztof Kaczmarski (Warsaw University of Technology)
- Kyeong Soo Kim (Xi'an Jiaotong-Liverpool University)
- Kazuhiko Komatsu (Tohoku University)
- Daniel Sundfeld Lima (University of Brasília)
- Takahiro Nishigaki (Takushoku University )
- Tomonobu Ozaki (Nihon University)
- Hiroyuki Sato (The University of Tokyo)
- Kazem Shekofteh (Heidelberg University)
- Takashi Shimokawabe (The University of Tokyo)
- Koichi Shirahata (Fujitsu Limited)
- Ryousei Takano (National Institute of Advanced Industrial Science and Technology (AIST))
- Nobuhiko Yamaguchi (Saga University)
- Tetsuya Yoshida (Nara Women's University)
