NVIDIA feels that the basic ideas behind CUDA are reinforced by OpenCL -- the basic model is the same, although OpenCL is a lower-level architecture that requires coders to do their own memory ...

I'm a bit confused about local memory, and hopefully someone can shine a light into my confusion! Brief problem synopsis: I have two sets of data, A and B. Both essentially consist of points in 3D ...

In high performance computing, machine learning, and a growing set of other application areas, accelerated, heterogeneous systems are becoming the norm. With that state come several parallel ...

With the new versions of CUDA, there's some latency hiding that helps you out, but you still need to watch out for copying large amounts of data between the CPU and GPU memory in the middle of ...

MemtestG80 and MemtestCL are a software-based testers to test for soft errors in GPU memory or logic for NVIDIA CUDA-enabled or OpenCL-enabled GPUs.

In terms of the benchmark results, the RTX 4070 notched up 202,437 points in Geekbench CUDA test and 177,594 in OpenCL, which are around 25-30% higher than scores racked up by the RTX 3070.

Opening up CUDA is the NVIDIA technology that allows applications to be run on the GPU, rather than the CPU, and take advantage of the superior parallel processing capabilities of the GPU.

On Linux, the ZLUDA developers have gotten benchmarks for a Core i5-8700K, scoring 6333 with CUDA using the onboard UHD 630 graphics compared to 6482 in OpenCL.

A CUDA core is a SIMD (Single Instruction, Multiple Data) processing unit found inside your Nvidia graphics card that handles parallel computing tasks; with more CUDA cores, comes the ability to ...