What is cudaMemset?

From online documentation: cudaError_t cudaMemset (void * devPtr, int value, size_t count ) Fills the first count bytes of the memory area pointed to by devPtr with the constant byte value value.

Does cudaMalloc initialize memory?

The memory is not cleared. So, you will need cudaMemset to initialize the memory.

For what purpose cudaMalloc function is used?

cudaMalloc is a function that can be called from the host or the device to allocate memory on the device, much like malloc for the host. The memory allocated with cudaMalloc must be freed with cudaFree.

Is cudaMemcpy synchronous?

1x “stream” on GPU (called the “default stream”). Most CUDA calls are synchronous (often called “blocking”). An example of a blocking call is cudaMemcpy(). 1.

What memory system is used in CUDA?

CUDA also uses an abstract memory type called local memory. Local memory is not a separate memory system per se but rather a memory location used to hold spilled registers. Register spilling occurs when a thread block requires more register storage than is available on an SM.

How does CUDA code work?

In CUDA, the host refers to the CPU and its memory, while the device refers to the GPU and its memory. Code run on the host can manage memory on both the host and device, and also launches kernels which are functions executed on the device. These kernels are executed by many GPU threads in parallel.

Why do I need CUDA?

The CUDA programming model allows scaling software transparently with an increasing number of processor cores in GPUs. You can program applications using CUDA language abstractions. Any problem or application can be divided into small independent problems and solved independently among these CUDA blocks.

Is cudaFree synchronous?

cudaFree() is synchronous. If you really want it to be asynchronous, you can create your own CPU thread, give it a worker queue, and register cudaFree requests from your primary thread.

What is CUDA synchronization?

There are two types of stream synchronization in CUDA. A programmer can place the synchronization barrier explicitly, to synchronize tasks such as memory operations. Some functions are implicitly synchronized, which means one or all streams must complete before proceeding to the next section.

How does CUDA unified memory?

Unified Memory combines the advantages of explicit copies and zero-copy access: the GPU can access any page of the entire system memory and at the same time migrate the data on-demand to its own memory for high bandwidth access.

How does CUDA managed memory work?

When code running on a CPU or GPU accesses data allocated this way (often called CUDA managed data), the CUDA system software and/or the hardware takes care of migrating memory pages to the memory of the accessing processor.