*Video Summary: OpenMP for GPU Programming* - *Introduction & Overview* - 0:01: Introduction of Michael Clem from AMD and OpenMP ARB. - 0:14: Focus on GPU programming with OpenMP API. - 1:22: Emphasis on productivity, portability, and distilling HPC into OpenMP API. - 2:19: Member organizations in OpenMP ARB. - *Agenda & Basics* - 3:06: Introduction of OpenMP device and execution model. - 3:54: Asynchronous kernels offloading and Q&A session. - *Example & Device Model* - 4:07: Running example of SAXPY from BLAS. - 6:14: Support for accelerators in OpenMP 4.0. - *Data Management* - 9:22: Offload regions and data environments. - 11:06: Host and device memory handling. - *Compiler Optimizations* - 15:40: Compiler's handling of local arrays and data transfer mechanisms. - 17:20: Performance optimizations like not transferring scalars back. - *Advanced Concepts* - 31:22: Block size and loop iterations. - 35:26: Main source of optimization is data transfer management. - *Synchronization & Dependencies* - 46:37: OpenMP synchronization mechanisms. - 47:56: Task dependency graph and execution. - *Interoperability & Features* - 49:19: APIs for memory management. - 50:42: Support for unified shared memory in OpenMP. - *Performance & Tools* - 1:02:04: Need for explicit control in data transfers. - 1:03:01: OpenMP's support for streams. - *Future Developments* - 1:05:54: OpenMP 6 to allow querying device types. - 1:09:16: Flexibility for data analytic workflows. - *Closing* - 1:12:45: Webinar concluded, thanks given.
What should i do if my my data arrays might be larger than the total GPU memory? Assuming i have a simple example C[i] = A[i] + B[i], where all three sizes together are larger than the GPU memory?
Tim Mattson suggested using #pragma omp loop instead of the "big ugly directive" #pragma omp target teams distribute paraller for simd. (See ua-cam.com/video/Rde6kpv16-4/v-deo.html)
Tim Mattson suggested using #pragma omp loop instead of the "big ugly directive" #pragma omp target teams distribute parallel for simd. (See ua-cam.com/video/Rde6kpv16-4/v-deo.html)
*Video Summary: OpenMP for GPU Programming*
- *Introduction & Overview*
- 0:01: Introduction of Michael Clem from AMD and OpenMP ARB.
- 0:14: Focus on GPU programming with OpenMP API.
- 1:22: Emphasis on productivity, portability, and distilling HPC into OpenMP API.
- 2:19: Member organizations in OpenMP ARB.
- *Agenda & Basics*
- 3:06: Introduction of OpenMP device and execution model.
- 3:54: Asynchronous kernels offloading and Q&A session.
- *Example & Device Model*
- 4:07: Running example of SAXPY from BLAS.
- 6:14: Support for accelerators in OpenMP 4.0.
- *Data Management*
- 9:22: Offload regions and data environments.
- 11:06: Host and device memory handling.
- *Compiler Optimizations*
- 15:40: Compiler's handling of local arrays and data transfer mechanisms.
- 17:20: Performance optimizations like not transferring scalars back.
- *Advanced Concepts*
- 31:22: Block size and loop iterations.
- 35:26: Main source of optimization is data transfer management.
- *Synchronization & Dependencies*
- 46:37: OpenMP synchronization mechanisms.
- 47:56: Task dependency graph and execution.
- *Interoperability & Features*
- 49:19: APIs for memory management.
- 50:42: Support for unified shared memory in OpenMP.
- *Performance & Tools*
- 1:02:04: Need for explicit control in data transfers.
- 1:03:01: OpenMP's support for streams.
- *Future Developments*
- 1:05:54: OpenMP 6 to allow querying device types.
- 1:09:16: Flexibility for data analytic workflows.
- *Closing*
- 1:12:45: Webinar concluded, thanks given.
Nice explanation.
55:03 shared memory utilization on Nvidia GPUs
What should i do if my my data arrays might be larger than the total GPU memory?
Assuming i have a simple example C[i] = A[i] + B[i], where all three sizes together are larger than the GPU memory?
At 31:54 there appears to be a mistake. The variable n is not defined.
Hey how can i contact you I have query
Tim Mattson suggested using #pragma omp loop instead of the "big ugly directive" #pragma omp target teams distribute paraller for simd. (See ua-cam.com/video/Rde6kpv16-4/v-deo.html)
Tim Mattson suggested using #pragma omp loop instead of the "big ugly directive" #pragma omp target teams distribute parallel for simd. (See ua-cam.com/video/Rde6kpv16-4/v-deo.html)