Can CUDA use shared GPU memory?
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This type of memory is what integrated graphics eg Intel HD series typically use. This is not on your NVIDIA GPU, and CUDA can’t use it. Tensorflow can’t use it when running on GPU because CUDA can’t use it, and also when running on CPU because it’s reserved for graphics.
How do I use more memory on my GPU?
Once you reach the BIOS menu, look for a menu similar to Graphics Settings, Video Settings or VGA Share Memory Size. You can typically find it under the Advanced menu. Then, up the Pre-Allocated VRAM to whichever option suits you best. Save the configuration and restart your computer.
What is Cuda cache?
These memories are called caches, and they can transmit data to the processor at a much higher rate than DRAM. But they are typically small in size. The modern GPU contains three levels of caching – L1, L2 and L3. The L1 cache has higher bandwidth compared to other L2 and L3 caches.
Does a GPU have a cache?
As seen above, all GPUs have a cache called L2 cache. And we know that within the CPU also there is a cache called L2 cache. Here also as with memory, size of L2 cache on GPU is much smaller than size of L2 or L3 cache on CPU.
Shared memory is allocated per thread block, so all threads in the block have access to the same shared memory. Threads can access data in shared memory loaded from global memory by other threads within the same thread block.
What is kernel in CUDA?
The kernel is a function executed on the GPU. CUDA kernels are subdivided into blocks. A group of threads is called a CUDA block. CUDA blocks are grouped into a grid. A kernel is executed as a grid of blocks of threads (Figure 2).
Does model Cuda transfer data to gpu0 or gpu5?
More specifically, model.cuda (5) transfers data onto GPU0 (the default), but the variable transfers do not, the variables seem to only go onto GPU5 when I specify the device number. Sorry, something went wrong. @lucylw Yes this is the intended behavior.
Why isn’t my cudafree working?
As a quick test, you can also run your code with cuda-memcheck (do that too.) As a result, you weren’t freeing anything, since you weren’t passing the correct pointer to cudaFree. If you had used proper CUDA error checking, you would know this already.
How does CUDA read and write data in a contiguous fashion?
The following simple CUDA kernel reads or writes a chunk of memory in a contiguous fashion. This benchmark migrates data from CPU to GPU memory and accesses all data once on the GPU. The input data ( ptr) is allocated with cudaMallocManaged or cudaMallocHost and initially populated on the CPU.
When should I use CUDA error checking?
You should always do proper CUDA error checking, any time you are having trouble with a CUDA code, preferably before asking others for help. It is not sensible to ignore information that the CUDA runtime is providing you to help understand your code. Thank you very much for pointing out this error.