Large-scale deep unsupervised learning using graphics processors
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Parallel simulation for parameter estimation of optical tissue properties
Euro-Par'10 Proceedings of the 16th international Euro-Par conference on Parallel processing: Part II
| Hi-index | 0.00 |
In the past, graphics processors were special-purpose hardwired application accelerators, suitable only for conventional graphics applications. Modern GPUs are fully programmable, massively parallel floating point processors. In this talk I will describe NVIDIA's scalable, highly parallel many-core GPU architecture and how CUDA software for GPU computing delivers high throughput for data-intensive processing. I will discuss how CUDA is reinvigorating research on data-parallel algorithms, reducing time to scientific discovery, and enabling a variety of compute-intensive industrial applications of GPUs beyond computer graphics.