I have two monitors hooked up to two different graphics processing units (GPUs), and I want the workload to be evenly distributed between them. However, this is not happening – even though the video is being displayed on the second monitor, all of the video decoding is being handled by the main GPU. I’ve searched online for similar problems, but none of the solutions I’ve found have addressed my specific issue.
Based on my Google searches, it seems like achieving the outcome I want is impossible – unless there is some specialized software that can help. The problem I’m trying to address in this question is how to select which GPU is used for each application. Unfortunately, Windows recommends using the same GPU for both power savings and maximum performance, which prevents me from using any available solutions to this problem.
I have two questions to ask:
- Is it feasible to make sure that the GPU connected to a particular monitor handles all rendering tasks?
- Can I manually select which GPU to use for specific power-saving profiles or other settings in Windows?
To provide some context, I have a GTX 1060 and a GT 730 graphics card, with one monitor connected to each GPU.
In modern computers, graphics processing units (GPUs) are used for a variety of tasks, including video decoding, gaming, and other high-performance computing tasks. However, when a computer has multiple GPUs, it can be challenging to determine which GPU is being used for a particular task. This can lead to inefficiencies and decreased performance, as tasks may be assigned to less capable GPUs.
In this blog post, we will explore the issue of manually picking which GPU is power efficient and which is high performance. We will discuss the challenges of assigning tasks to specific GPUs and explore potential solutions to this problem.
Understanding GPU Assignment
When a computer has multiple GPUs, the operating system must decide which GPU to use for a given task. In most cases, the operating system will automatically assign tasks to the most capable GPU. However, this may not always be the best choice, as different GPUs have different strengths and weaknesses.
For example, some GPUs may be better suited for power efficiency, while others are designed for high-performance computing. Additionally, some GPUs may be better at specific tasks, such as video decoding or gaming.
In order to ensure that tasks are assigned to the most appropriate GPU, it is important to understand how GPU assignment works. This involves understanding how the operating system determines which GPU to use for a given task, as well as the factors that can influence this decision.
Enforcing Rendering with a Specific GPU
One potential solution to the problem of manually picking which GPU is power efficient and which is high performance is to enforce rendering with a specific GPU. This would involve instructing the operating system to use a specific GPU for a given task, regardless of its capabilities.
While this approach may be effective in some cases, it is not always practical. In order to enforce rendering with a specific GPU, the software used for the task must support this feature. Additionally, this approach may not be effective for tasks that require the use of multiple GPUs, such as some gaming applications.
Manually Selecting a GPU for Power Saving or Other Profiles
Another potential solution to the problem of manually picking which GPU is power efficient and which is high performance is to manually select a GPU for power saving or other profiles. This would involve instructing the operating system to use a specific GPU for tasks that require power efficiency, while using a different GPU for tasks that require high performance.
While this approach may be more flexible than enforcing rendering with a specific GPU, it is still subject to the limitations of GPU assignment. In order to effectively use this approach, it is important to understand the capabilities of each GPU and the tasks for which they are best suited.
Using Third-Party Software for GPU Assignment
Another potential solution to the problem of manually picking which GPU is power efficient and which is high performance is to use third-party software for GPU assignment. This software can help to optimize GPU usage by assigning tasks to the most appropriate GPU based on their requirements.
There are several third-party software options available for GPU assignment, including NVIDIA Optimus and AMD Switchable Graphics. These programs can help to improve performance and efficiency by automatically assigning tasks to the most appropriate GPU.
In conclusion, manually picking which GPU is power efficient and which is high performance can be a challenging task. However, by understanding the factors that influence GPU assignment and exploring potential solutions, it is possible to optimize GPU usage for improved performance and efficiency. Whether through enforcing rendering with a specific GPU, manually selecting a GPU for power saving or other profiles, or using third-party software for GPU assignment, there are several options available for improving GPU performance and efficiency.