3dGameMan | Intel Xe GPU Patch for Shared Virtual Memory #news #intel #gpu #patch #fix @3DGAMEMAN @3DGAMEMAN | Uploaded 2 weeks ago | Updated 1 day ago
3dGameMan T-Shirts: https://3dgameman.myspreadshop.com/all
Join our community: https://www.PATREON.com/3dGameMan
- Tip Jar: https://paypal.me/3dGameMan
- Channel Perks: https://www.youtube.com/channel/UCiDQxvfJlZ8hpE1IoWZ63bA/join
- Thanks for liking, sharing, subscribing & hitting that notification bell :)
- Have a Question?: https://youtu.be/pIxzR4jUzbg
Other relevant links:
Twitter: https://www.twitter.com/3dGameMan
Steam: https://steamcommunity.com/id/3dGameMan
TikTok: https://www.tiktok.com/@3dGameMan
Article: https://www.phoronix.com/news/Intel-Xe-GPU-SVM-RFC-Patches
Intel has released new patches to enhance the GPU Shared Virtual Memory (SVM) support in their Xe graphics driver. This is a significant step towards improving the performance and flexibility of Intel's integrated graphics solutions.
What is GPU Shared Virtual Memory?
GPU SVM allows for seamless memory sharing between the system's CPU and GPU. This can lead to improved performance and programming flexibility, as applications can access and manipulate data more efficiently.
Key benefits of GPU SVM:
Improved performance: Applications can leverage the GPU's parallel processing capabilities more effectively.
Increased flexibility: Developers have more control over memory allocation and management.
Reduced overhead: Less context switching between CPU and GPU.
Intel's progress:
The latest patches build the GPU SVM layer for the Xe driver and expose a new user-space API.
The initial version supports GPU page faults for system allocations, runtime allocations, migration to/from vRAM, and unified eviction handling.
Intel has successfully tested this SVM code on various Xe hardware, including Lunar Lake, Battlemage, and Ponte Vecchio.
Future plans:
Intel plans to add support for multi-GPU configurations, user pointer handling, and madvise and prefetch IOCTL handling.
This is a positive development for Intel's graphics solutions, as GPU SVM is a crucial feature for modern applications and workloads.
3dGameMan T-Shirts: https://3dgameman.myspreadshop.com/all
Join our community: https://www.PATREON.com/3dGameMan
- Tip Jar: https://paypal.me/3dGameMan
- Channel Perks: https://www.youtube.com/channel/UCiDQxvfJlZ8hpE1IoWZ63bA/join
- Thanks for liking, sharing, subscribing & hitting that notification bell :)
- Have a Question?: https://youtu.be/pIxzR4jUzbg
Other relevant links:
Twitter: https://www.twitter.com/3dGameMan
Steam: https://steamcommunity.com/id/3dGameMan
TikTok: https://www.tiktok.com/@3dGameMan
Article: https://www.phoronix.com/news/Intel-Xe-GPU-SVM-RFC-Patches
Intel has released new patches to enhance the GPU Shared Virtual Memory (SVM) support in their Xe graphics driver. This is a significant step towards improving the performance and flexibility of Intel's integrated graphics solutions.
What is GPU Shared Virtual Memory?
GPU SVM allows for seamless memory sharing between the system's CPU and GPU. This can lead to improved performance and programming flexibility, as applications can access and manipulate data more efficiently.
Key benefits of GPU SVM:
Improved performance: Applications can leverage the GPU's parallel processing capabilities more effectively.
Increased flexibility: Developers have more control over memory allocation and management.
Reduced overhead: Less context switching between CPU and GPU.
Intel's progress:
The latest patches build the GPU SVM layer for the Xe driver and expose a new user-space API.
The initial version supports GPU page faults for system allocations, runtime allocations, migration to/from vRAM, and unified eviction handling.
Intel has successfully tested this SVM code on various Xe hardware, including Lunar Lake, Battlemage, and Ponte Vecchio.
Future plans:
Intel plans to add support for multi-GPU configurations, user pointer handling, and madvise and prefetch IOCTL handling.
This is a positive development for Intel's graphics solutions, as GPU SVM is a crucial feature for modern applications and workloads.
