If you have purchased a graphics processing card (GPU) manufactured by NVIDIA in recent years, you have most likely received one that contains CUDA cores. Is this a positive? What’s the difference between CUDA cores and regular CPU cores? How significant are CUDA cores for industrial GPU computing?
This article will supply the answer!
What are CUDA Cores?
Standing for Compute Unified Device Architecture, CUDA cores are the processing units located within a GPU. The “CUDA” term was used to highlight the system’s parallel computing capability, along with the APIs used to access NVIDIA’s instruction set. While you may have only noticed CUDA cores recently, they were first launched all the way back in 2006. Since then it has become an integral component in GPUs – and, ultimately, for high-performance computers.
How do CUDA Cores Differ From Other Cores?
While it shouldn’t come as a surprise, CUDA cores are different from other computer-based cores like CPU cores and tensor cores. Below is a quick rundown of the main differences:
- CUDA cores are highly parallel. As a result, they are able to perform numerous tasks simultaneously.
- These cores are specifically designed for algorithms that are capable of being parallelized.
- Large amounts of data can be accessed with ease and speed. This is due to them featuring high memory bandwidth.
Compared to other cores, it’s true that CUDA cores are more centralized in a specific area. However, this approach does supply a large performance boost with certain application types. These applications can include everything from deep learning to time-sensitive workloads.
The Benefits of CUDA Cores for Industrial GPU Computing
As seen at Things Embedded (a specialist computer engineering company), CUDA cores are often a component considered for industrial computer systems. Yes, it is only appropriate for certain applications. Yet when it is suitable, CUDA cores supply major benefits for industrial GPU computing – and that’s why they are one of the first considerations for a bespoke system.
The most obvious and important benefit is the added power CUDA cores supply. By being able to comfortably handle multiple tasks at the same time, it can increase performance not just for computer graphics but also general computer based tasks. In fact, each core has the capability to process multiple threads with efficiency and simultaneously.
An extension of this is that intensive applications can profit from significant speedups. When in an industrial setting (where demands are high and constant), this added processing capability can make all the difference. CUDA cores are also helpful with modern parallel processing tasks, namely artificial intelligence and machine learning. When a computer’s graphics card features a high number of CUDA cores, it helps with the performance of such tasks.
Going back to the question posed at the top of the article. When you factor in how important AI and machine learning are for modern industrial processes, it goes without saying that CUDA cores are significant for industrial GPU computing – and that’s putting it mildly.