What are streaming multiprocessors?

The streaming multiprocessors (SMs) are the part of the GPU that runs our CUDA kernels. Each SM contains the following. Thousands of registers that can be partitioned among threads of execution. Several caches: – Shared memory for fast data interchange between threads.

What is a warp in GPU architecture and what is the major constraint of its operation?

A warp is a collection of threads, 32 in current implementations, that are executed simultaneously by an SM. Multiple warps can be executed on an SM at once. The threads of a thread block execute concurrently on one SM, and multiple thread blocks can execute concurrently on one SM.

How many streaming multiprocessors are there?

13 Streaming Multiprocessors
For the GTX 970 there are 13 Streaming Multiprocessors (SM) with 128 Cuda Cores each. Cuda Cores are also called Stream Processors (SP). You can define grids which maps blocks to the GPU. You can define blocks which map threads to Stream Processors (the 128 Cuda Cores per SM).

What is a CUDA kernel?

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).

What are CUDA warps?

A warp is a set of 32 threads within a thread block such that all the threads in a warp execute the same instruction. These threads are selected serially by the SM. Once a thread block is launched on a multiprocessor (SM), all of its warps are resident until their execution finishes.

How do CUDA kernels 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.

What is CUDA texture memory?

TEXTURE MEMORY. Read only memory used by programs in CUDA. Used in General Purpose Computing for Accuracy and Efficiency. Designed for DirectX and OpenGL rendering Pipelines.

What is CUDA draw and explain Cuda architecture in detail?

Introduction. NVIDIA® CUDA™ technology leverages the massively parallel processing power of NVIDIA GPUs. The CUDA architecture is a revolutionary parallel computing architecture that delivers the performance of NVIDIA’s world-renowned graphics processor technology to general purpose GPU Computing.

How does CUDA work with multiple processors?

When a CUDA program on the host CPU invokes a kernel grid, the blocks of the grid are enumerated and distributed to multiprocessors with available execution capacity. The threads of a thread block execute concurrently on one multiprocessor, and multiple thread blocks can execute concurrently on one multiprocessor.

What is the thread / block layout in CUDA?

The thread / block layout is described in detail in the CUDA programming guide. In particular, chapter 4 states: The CUDA architecture is built around a scalable array of multithreaded Streaming Multiprocessors (SMs).

What is the difference between SM and Warp in CUDA?

A SM may contain multiple blocks. Each block may contain several threads. A SM have multiple CUDA cores (as a developer, you should not care about this because it is abstracted by warp), which will work on thread. SM always working on warp of threads (always 32). A warp will only working on thread from same block.

How many CUDA cores does a single SM have?

Each SM contains 8 CUDA cores, and at any one time they’re executing a single warp of 32 threads – so it takes 4 clock cycles to issue a single instruction for the whole warp.