Darknet on OpenCL on Windows 11 x64

Hi, there are many challenges on Windows 11 x64 with AMD Radeon RX 6900 XT. For the last few months, from time to time, I started to try to build on Windows 10 x64 first and later I updated to Windows 11 x64. There are the following open issues I faced: 1) Time spent on detection is a bit longer than on GNU/Linux or macOS. 2) Detections seem fine when I try Continue ReadingDarknet on OpenCL on Windows 11 x64

GPU-Computing macOS Big Sur vs iBuntu Lux Sur

Hello, Let’s test this beauty from the last post on… LuxMark ;-). The thing is that I wanted to compare OpenCL. I know that OpenCL in both systems is not working entirely right. I found on macOS that (multi-GPU case) clFinish(q) is slow down each time, on iBuntu -cl-fast-relaxed-math causes a black-scenes on Lux Ball… and on Darknet on OpenCL it is more things wrong, but maybe there are my bugs, so… Continue ReadingGPU-Computing macOS Big Sur vs iBuntu Lux Sur

Mac Moria Miner Project Failure

Hello, every failure is a lesson, so let me describe my experiment and the story behind it… I dream about the most robust possible GPU-computing macOS. Let’s start with hardware… design, the way it looks, is not a design, so let’s name it the look and feel ;-). I am sorry to Apple, please forgive me. This was only for tests and future, again try, Ph.D. studies. Do not look at it Continue ReadingMac Moria Miner Project Failure

GPU-Computing for Vision Recognition Platform as IoT

Hi, my dear readers. Today I would like to tell you three technical stories. It will be stories with a happy ending… and you know me..? I am unsure if that story happens precisely this way, but the story is true. IoT Idea Story ;-). First of all, you probably know my passion for IoT? And also, as a tool builder, sorry to say, I do not like to buy the software Continue ReadingGPU-Computing for Vision Recognition Platform as IoT

DarkNet-vNext on CUDA

Hello, I know that many people like my DarkNet on OpenCL. Recently I also made an improved version of the original DarkNet on CUDA, and I called it DarkNet-vNext, and it has all improvements that you were probably looking for. All Yolo models are supported from the 1st to the 4th version. It supports OpenCV 4 and, for example, benchmark possibility. The good news is it is high-speed. As you probably know, Continue ReadingDarkNet-vNext on CUDA

The Multi-GPU-SET Idea

Hello, I am a Ph.D. student in Poland at the Silesian University of Technology. And I wanted to start a general discussion on the classifier on the video stream improvement idea. I called it the “Multi-GPU & Multi-SET” or, in short, the “Multi-GPU-SET” idea. People use Multi-GPU and the “Syncing” for Convolutional Neural Networks. But nobody, in my opinion, tried multi-GPU to classify. So what is it about? Well, it is about Continue ReadingThe Multi-GPU-SET Idea

GPU OpenCL Fine-Tuning Problem Solution

Hello, after about half-year, I at last found the solution to the biggest optimization issue I had so far in the Darknet on OpenCL solution. It was tough to solve, and I even wrote at the AMD Community Post. Today very early morning, I posted on that post solution shown below. CPU CODE THAT INVOKES THE GPU CODE AND USES BOTH GLOBAL AND LOCAL THREAD SPACES! GPU CODE THAT IS ACCELERATED WITHOUT Continue ReadingGPU OpenCL Fine-Tuning Problem Solution

PhD Progress from May 27th 2020 Update Keynote

Hi, This video was recorded today and shows my Ph.D. first year of study effects in detail. The first on the planet… Multi-GPU & Multi-SET image classification pattern… so, I wish you a happy watch! Thanks for watching! p ;).

PhD OpenCL Challenges

Hi, I want to show you code samples for OpenCL that may be important when you start with this great graphics card computing (GPU-computing) library. The goal is to make code as good as possible on any platform that supports OpenCL and on GPUs from AMD, Intel, NVidia, and Mali on CPUs from AMD, Intel ARM. All examples are from the Darknet on OpenCL port I did some time ago. The first Continue ReadingPhD OpenCL Challenges