@dheerajyadav3034

Out of the many videos for GPU/CPU, this video saved my time as well as loved the simplified story. Thanks Alex & IBM

@KingsleyOkeze

Having an exam in 2 hours time and I'm here to know a killer explanation of a GPU. Thanks for this.

@Newbport849

Finally a more layman's terms video on the subject, thanks!

@arounaalaho6357

"Gaming is no longer the focus of GPUs anymore"! 
Thanks guys

@TonyCalice

This educational video is one of the reasons I love the Internet.  Thank you Alex for doing this and you answered the question: 1) what is a GPU, and 2) why parallel processing is important?

Would love to see this presentation further explain: 1) what does my solution delivery team need to do in order to leverage parallel GPU processing, 2) how do I integrate a GPU processing within my current architecture and 3) what challenges do traditional solutions have with leveraging GPU capabilities?

@wireghost897

IBM dev rels are the best when it comes to explaining stuff...

@josemedeiros007

Great explanation , I was also a IBMer working in IBM Global Services in 1996 -1998. When I first learned Windows NT 3.51 server in 1996, Microsoft stated that it uses Symmetrical Processing "SMP" in utilizing more then one CPU on a server.

@Old299dfk

Can we all just take a second to appreciate how easy this woman makes writing reversed look? 

She doesn't even bat an eye!

@Cyber_Vigilante_Jonathan

I love IBM, I'm holding the IBM Certified Cyber Security Analyst Professional Certificate and the experience was awesome throughout the 8 coursed

@EdwinLjunggrenGraslund

The most impressive thing about this video is how you had to draw everything backwards. How did you do that without it looking like crap

@gemini_537

Gemini 1.5 Pro: This video is about GPUs, explained by Alex Hudak, an offering manager at IBM.

The video starts with a basic question: what is a GPU? GPUs are graphic processing units, in contrast to CPUs (central processing units). CPUs are made up of just a few cores and perform computations in a serial form, one at a time. GPUs, on the other hand, are made up of hundreds of cores and can perform computations in parallel, making them ideal for intense computations. GPUs are especially useful for graphic intensive applications such as VDI (virtual desktop infrastructure) and movie animation/rendering.

Another big application of GPUs is in artificial intelligence (AI), including machine learning and deep learning. There are GPUs specifically designed for inferencing for machine learning purposes and for training neural networks. GPUs are not always necessary for high performance computing (HPC) but they are an important part of it. HPC applications can be very compute intensive and GPUs can be added to servers to spread out the workload.

The video then discusses why GPUs are important for cloud computing. GPUs are expensive and constantly being updated with new technology, so itโ€™s impractical for companies to keep up with the latest tech on their own. Cloud providers, however, can continually update their technology and provide GPUs to companies when they need them. There are two main types of cloud server infrastructure: bare metal and virtual servers. Bare metal infrastructure allows companies to access the entire server and customize the configuration, whereas virtual servers are more flexible and can be a better option for companies that only need GPUs in short bursts.

In conclusion, GPUs are powerful tools for graphic intensive applications, AI, and HPC. Cloud computing allows companies to leverage GPUs without the burden of maintaining their own expensive infrastructure.

@RednetworkblogNetPlus

1:22: Your "serial" explanation is horrendously inexact. CPUs are able to do computations in parallel when they are multicore. The main difference between GPUs and CPUs is CPUs have many less cores than GPUs ( You got that right ) and that GPU cores are highly specialized. Moreover, you gave a pretty shallow explanation about GPUs. This video is more about comparing use cases between CPUs and GPUs for cloud computing. Your title is misleading.

@achioterojo8819

I study it and nowhere I found this good videos, IBM is awesome

@venkatadesai7157

Amazing explanation. Thank you so much for bringing in the clarity on CPU vs GPU.

@KiranPhaneendran

The best and easy to understand explanation so far. Thanks!

@JaimeCastillo-o4f

Wow, I had a very vague (and wrong, lol) idea of what a GPU was. It actually makes sense for me now.

@Alsteraib985

Alexandra Hudak and GPUs, I'm in love.

@awichichedi3382

I've been looking for a good video 
And finally I found the best one 
Thanks a lot ๐Ÿ’“

@mjames2117

Writing backwards in real time whilst multi tasking and multi processing is seriously impressive

@akwiseguy

That's cool how you write backwards so neat