A Survey on Deep Learning Hardware Accelerators for Heterogeneous HPC Platforms
Politecnico di Milano · University of Bologna · +9 more institutions
Abstract
Recent trends in deep learning (DL) have made hardware accelerators essential for various high-performance computing (HPC) applications, including image classification, computer vision, and speech recognition. This survey summarizes and classifies the most recent developments in DL accelerators, focusing on their role in meeting the performance demands of HPC applications. We explore cutting-edge approaches to DL acceleration, covering not only GPU- and TPU-based platforms but also specialized hardware such as FPGA- and ASIC-based accelerators, Neural Processing Units, open hardware RISC-V-based accelerators, and co-processors. This survey also describes accelerators leveraging emerging memory technologies and…
Citation impact
- FWCI
- 38.74
- Percentile
- 100%
- References
- 206
Authors
22Topics & keywords
- Computer science
- Deep learning
- Computer architecture
- Operating system
- Embedded system
- Computer hardware
- Artificial intelligence