It has become very common nowadays to have shared GPU memory. But what exactly does this memory do? What is the basic requirement to have shared GPU memory? Well, if you have a computer with an integrated GPU or even if it is dedicated, the computer makes sure to reserve half of your RAM for the GPU. As GPU is one of the most RAM-consuming components present in the computer after the CPU. GPUs are majorly focused on providing support to graphics-related software and applications.
For example, 3D modeling and rendering software are one of those types. In such cases, the images, videos & graphics used in the software come with a very high resolution which requires potential support in terms of graphics. And the GPU is used for the same. At the same time, the GPU also needs memory support to store the processing data and files and execute them. And that’s why the computer makes sure to reserve half of the RAM storage for the GPU. In today’s article, we’ll learn everything about shared GPU memory.
What is Shared GPU Memory?
In every GPU, there is a dedicated video memory which helps the high graphic software or application to run efficiently. And this type of memory is physically available in the graphics card itself. Whereas, sometimes this video memory is not enough for some software which can lead to the crash of the application, or sometimes it may lag or won’t even run properly.
In such cases, the shared GPU memory provides the graphical storage support to that software in order to make the most out of it. In simple terms, the shared GPU memory is a type of virtual RAM which is reserved from the actual RAM of your computer itself. This shared GPU memory is only used when there is a requirement by the GPU. In general, this type of shared GPU memory is also known as VRAM (Video RAM) and the same can be used once you run out of your dedicated GPU memory.
How Does It Work?
Let’s understand the working of shared GPU memory step by step. Firstly every GPU has its own video memory for processing the task. Unlike the CPU, the GPU has many graphics task processing in the background, and that too at the same time to render the graphics.
And if discussed, a single rendering execution cycle, includes processing multiple lightning elements, shading, and enhancing the texture to achieve the given task. And just like any other process, these all require storage to store the files, which is necessary at the time of execution. Manier times, the dedicated video memory is not enough for processing all these high-rendering tasks, and that is where the shared GPU memory comes into the frame.
Shared GPU memory is a virtual shared memory that allows the GPU to store the remaining processing data, in order to maintain smooth functioning and create a proper pipeline of tasks for the GPU. Unlike the video memory of the GPU, the shared GPU memory is not physically available.
Instead, it is actually allocated memory from the RAM, which helps the GPU in processing whenever there is a requirement. A user can utilize up to 50% of the actual RAM present in the system to use it as a shared GPU memory. A shared GPU memory can be configured regardless of system type, whether it is a shared GPU or integrated.
What is the Difference Between Shared Memory and Dedicated Memory?
When discussing shared memory and dedicated memory, the most important point which makes the major difference is their processing speed. As the dedicated memory is directly mounted with the GPU, it has very close links with its processing core and is also a part of GPU modules. Which eventually makes it a very fast processing memory. Whereas the shared memory is actually a partition of RAM that has to connect with the GPU using PCIe connectors. Which automatically affects the performance of the GPU.
Also, whenever a user tries to utilize a shared GPU memory, it eventually disconnects up to 50% of RAM storage from other tasks, which has a direct effect on the performance of other components using RAM. whereas the GPU’s dedicated memory doesn’t follow the same working protocol. Due to its close links with the processing cores, it makes the task execution very fast, which cannot ever be matched with the shared GPU memory.
Does Your Shared GPU Memory be Increased or Decreased?
Compared to the performance parameters, the shared GPU memory does not directly affect it. To simplify it, let’s take an example of dedicated GPUs. For a dedicated GPU, even if you try to allocate maximum storage from RAM to be shared GPU memory, it won’t affect the performance. Unless and until the dedicated memory is completely filled up.
Once the dedicated storage is full then only the OS allows the system to use the shared memory. In simple terms, the dedicated GPU does not use any shared memory space unless the dedicated memory is completely full. Whereas even after that, if the shared memory is used, it won’t affect the performance as the system automatically reduces the frame rates and makes execution stable.
Whereas integrated GPU users often try to increase their dedicated or reserved storage by configuring the BIOS setting and registry editor for the best performance. But in reality, it can decrease the performance ratio, because in integrated GPUs, the system reserves a certain amount of space for the GPU. When the user tries to increase the dedicated memory storage, it reduces the space in RAM, degrading the performance.
For example, if your system has a RAM of 6GB and you want to increase the dedicated GPU storage by 2GB, then only 4GB of RAM will be available for you to use. Even if the system is in idle mode and the GPU is not still processing any task, the GPU will reserve 2GB of RAM. In such cases, it is always advised to have a shared GPU memory which is only accessible when there is a requirement.
What are the Advantages and Disadvantages of Shared GPU Memory?
Shared GPU memories are very useful if a user is trying to manage the performance for exceptional cases, as the shared GPU memory does not actually have any amount of storage unless and until there is a requirement.
The other options block the specific amount of storage from the RAM and cannot be accessed even if the system is in an idle position. The shared GPU memory does not require any physical space as it is a type of virtual storage, and it is actually allocated from RAM itself. The shared GPU memory can use up to 50% of RAM depending upon the user’s necessity and requirement.
On the other hand, the shared GPU memory is quite slower than the dedicated GPU memory. As the shared GPU memory is connected with the GPU via PCIe, which makes the processing quite complicated. The GPU has to transfer the data to the shared memory using PCIe, which takes effort and time. Due to this, it eventually creates a minor disturbance for the execution of the task.
Shared GPU Memory – FAQs
Ans: The need for shared GPU memories occurs only without dedicated memory. Devices such as laptops or low-config desktops with no dedicated video memory require shared GPU memory to provide graphic memory processing support. The shared memory is generally used only in integrated systems where the GPUs are directly connected to the motherboard or CPU.
Ans: In major cases, the limits of shared GPU memory is predetermined by the system manufacturer. On the other hand, the shared GPU memory limits can also be identified by the BIOS settings present in the system. In general, it depends on the total capacity of the RAM and how much allocation will be idle distribution based on the factors such as display resolution, etc.
The GPU driver configuration is also one method to identify the storage.
Ans: Yes, there is one alternative option available to the shared GPU memory is dedicated GPU memory which comes in the form of a graphics card. These graphic cards are faster than RAM in processing the data. Specifically for the GPU, graphics cards are always the best option if they are used for 3D modeling and rendering software or even for high-graphics games.
Ans: The basic requirement for using the shared GPU memory is that a system should support shared memory configuration or be compatible with the integrated graphics solution. The other factors which might affect the most are the motherboard, GPU, and chipset should be capable of working along with the shared memory configurations. Whereas the process is done with the help of GPU configuration drivers and OS, which allocates the memory from the RAM to the shared GPU memory.
