| Title |
Understanding GPU Architecture |
| Abstract |
In preparing application programs to run on GPUs, it can be helpful to have an understanding of the main features of GPU hardware design, and to be aware of similarities to and differences from CPUs. This roadmap is intended for those who are relatively new to GPUs or who would just like to learn more about the computer technology that goes into them. No particular parallel programming experience is assumed, and the exercises are based on standard NVIDIA sample programs that are included with the CUDA Toolkit. |
| Authors |
['Steve Lantz'] |
| Expertise Level |
None |
| Learning Outcome |
None |
| Learning Resource Type |
asynchronous online training |
| Target Group |
['Researchers', 'Research groups', 'Student'] |
| Keywords |
['GPU', 'architecture', 'memory', 'cache', 'V100', 'RTX 5000', 'bandwidth', 'tensor cores'] |
| Cost |
None |
| Duration |
240 |
| Language |
en |
| License |
None |
| Resource URL Type |
URL |
| Start Datetime |
None |
| URL |
https://cvw.cac.cornell.edu/gpu-architecture |
| Version Date |
2023-05 |
| Provider ID |
urn:ogf.org:glue2:access-ci.org:resource:cider:infrastructure.organizations:898 |
| Rating |
None |
