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Let's learn about Gpu via these 62 free blog posts. They are ordered by HackerNoon reader engagement data. Visit the /Learn or LearnRepo.com to find the most read blog posts about any technology.
A GPU (Graphics Processing Unit) is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer. It matters significantly beyond graphics for parallel processing tasks like AI, machine learning, and scientific simulations, driving advancements in computational power.
Which is the best GPU in 2021? If you are going to buy a powerful graphics card for gaming or cryptocurrency mining, here are our top picks from Nvidia and AMD.
Programming CUDA using Go is a bit more complex than in other languages. Although there are some excellent packages, such as mumax, the documentation is poor, lacks examples and it’s difficult to use.
A big question for Machine Learning and Deep Learning apps developers is whether or not to use a computer with a GPU, after all, GPUs are still very expensive. To get an idea, see the price of a typical GPU for processing AI in Brazil costs between US $ 1,000.00 and US $ 7,000.00 (or more).
More recently on my data science journey I have been using a low grade consumer GPU (NVIDIA GeForce 1060) to accomplish things that were previously only realistically capable on a cluster - here is why I think this is the direction data science will go in the next 5 years.
The best way to find a VR ready graphics card is to simply look at the Oculus Link requirements or PC requirements for individual VR games on Steam. On the low-end, you should at least aim for a GEFORCE GTX 970.
HBO's Silicon Valley imagined data compression with Pied Piper. Fast forward to 2024, and real-world startups like SQream Blue are making that dream a reality.
Artificial intelligence has become critical for various industries. Selecting appropriate processors and graphics cards will enable the best performance.
This isn't going to cover every single graphics card used in the whole world as there are so many. But we are going to be covering the one company that almost run the whole production and lead the market with a storm. Side note for the Nvidia side the cards I have added are all the main board cards from Nvidia themselves and not custom boards like which MSI and Asus make.
Many Deep learning or Machine Learning projects require GPU acceleration, and getting access to external GPUs or using GPU services by different cloud services can be costly, especially for students.
Demand for accelerated computing brings a large environmental impact. Remote GPU software will sharply reduce that impact via higher utilization of GPUs.
"I think it will be maybe the most precious commodity in the world," says Sam Altman on the Lex Fridman Podcast. "Compute is going to the currency of the future
We’ve seen image inpainting, which aims to remove an undesirable object from a picture. The machine learning-based techniques do not simply remove the objects, but they also understand the picture and fill the missing parts of the image with what the background should look like. The recent advancements are incredible, just like the results, and this inpainting task can be quite useful for many applications like advertisements or improving your future Instagram post. We also covered an even more challenging task: video inpainting, where the same process is applied to videos to remove objects or people.
NVIDIA has released three versions of the RTX 6000 Blackwell — and it’s precisely the Server Edition that turned out to be the most mysterious. We tested it in
With two common buzzwords in AI being Graphics Processing Unit (GPU) and Batch Processing, there is widespread need to run AI efficiently in production.
Take a deeper dive into what a GPU is, when you should use it or shouldn’t for Deep Learning tasks, and what is the best GPU on-premises and in the cloud in 202
The decentralized model not only supports cost-efficiency with a cost reduction of up to 70% for training AI models, but also fosters an inclusive environment,
The Reds or the Greens? What are the technologies behind? Cool AMD and cooler Nvidia, or vice-versa? Which one makes the most money out of the buck? Answering all these questions in the following article and sharing tips on how to get the best GPU!
AMD is likely going to be the next GPU of choice for nearly a quarter of HackerNoon readers that participated in a recent poll conducted on our website.
Discover how combining machine learning with microservices architecture enables scalable, high-performance systems by leveraging modular design, efficient data
By taking advantage of the parallel computing capabilities of GPUs, a significant decrease in computational time can be achieved relative to traditional CPU
A developer's log on fixing laptop VRAM overheating during AI workloads. Why Memory Junction hits 105°C and how Pulse Throttling solves it without undervolting.
This isn't going to cover every single graphics card used in the whole world as there are so many. But we are going to be covering the one company that almost run the whole production and lead the market with a storm. Side note for the Nvidia side the cards I have added are all the main board cards from Nvidia themselves and not custom boards like which MSI and Asus make.
