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?
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.
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 it’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.
Don't you think that it's much more likely that they simply mirrored the video along the vertical axis? I think so, because it's much more likely that she's right-handed instead of left-handed. BRAINZ
Wow - I can't begin to tell you how enlightening this short video was. It has, in 8mins, shed great light onto two MSc modules I'm working through right now: Blockchain (PoW mining) and Cloud Systems. I came for the blockchain mining but stayed for the relevance to cloud and virtualizaiton. 5 *s.
In summary, GPUs are focused on matrix computations in order to create images. CPUs execute more general and more complex instructions. A CPU is like a musician that can read and write music. A GPU is like a musician that knows specific chords.
People are trippin! Certainly not a bad video, but far from best. Everything can be summed up in less than 2 lines why 7 min!: GPU's have more cores than CPU and are thus able to handle compute intensive tasks. You can choose to have your own gpu infrastructure, or pay cloud-based resources. To call this a stellar explanation of GPU's is simply not acceptable! I have said my piece
Thank you for your good explain. May be, I can understtand the defference between CPU & GPU. But I have more question. from your direction ,Writing the keywords was very difficult?
Got to load off this question off my mind: Why don't we just have a cpu that has the capability of gpu and cpu at the same time? Like a god processor or something
If a GPU is so great at everything then why is it not used in place of a CPU. Is it because the OS is stuck with some architecture that only works with a CPU or cpu brands (Intel / amd) or is there some other reason.
Hi @indrajeet500 thanks for reaching out. GPUs have the capability of processing particular applications far faster than CPUs, but GPUs lack the some of the core functionality of CPUs which are needed for modern operating systems. GPUs are most suited for intensive compute applications such as low-latency graphics and deep learning, whereas CPUs are built for everyday computing. For now, GPUs and CPUs are a robust team!--Alex
In my learning from what I understand and how I explain it to people in a cliff notes version. Is that the CPU is quicker at writing out the equation, the GPU is quicker at coming up with the answer. I know it is a little thin but it seems to fit the description.
Technically, when you make an operating system, everything must executed in order. You can't do that in GPU because it's parallel processor. Therefore, you need serial processor (in this case CPU)
@@neamam9228 complex arithmetic calculations, GPU are best for simple calculations that are computationally intensive such as graph traversal, encryption and decryption
3:44 “[AI] is something that a CPU cannot do on its own.” That’s not off the wall but not really true. I ran mistral 7b with cpu using hugging face. If I get it from source, I do need NVIDIA gpus based on the way the code is set up. You can do a lot of great AI on CPU though.
Great video on clarification! ...Also are we NOT going to address the fact that the presenter has been writing in REVERSE for the purpose of this lesson?
Good video... although... It needs just a 'minor' correction--- CPU's can have only 1 core... the cores run in Parallel (not serie) the core in the GPU usually run in slower speed than the CPU cores... (there are a number of technical reasons for this limitation...) the big difference is that the specialization the GPU was initially developed for a specific task (as the name states) and as the goal was mainly graphics calculation (although it can be used for others... now AI, ML, ...) it has a small and specific set very math-oriented... It shines in any task where there are the possibility of using a distributed load (a bunch of simple tasks, remember these are simplistic cores) that can tun in parallel and spread the load for the GPU... ;-)
I agree that mistakes were made, but it's not right to say _"CPUs can have only 1 core... the cores run in parallel"._ As she said, a CPU can have one or many cores, but usually much less than the GPU. Also, the parallel vs series argument is quite strange. The OS manages multithreading which can mean that a program can run in parallel on a CPU. The same is true for a GPU (This is where I disagree with the lady in the video). But I agree with her in saying that GPUs are specifically designed and suited to tasks that run in parallel, while CPUs can do both well.
Good comment! it makes me clear the point that if GPU is fast why we need CPU, the main difference is that GPU's core is simplistic cores, doing specific tasks and running at a slower speed than the CPU.
More of an advert for compute services than an explanation of GPUs. Offload of graphics video rendering is certainly a thing but construction was a poor example, nobody live renders the CADD model, it wouldn't even be legal in many cases for permitting and engineering certification reasons, they used fixed plans that have been hashed and recorded and any field changed are appended. The laptop has plenty of GPU to display the approved fixed graphics.
Hi Tom! An Offering Manager is responsible for the full lifecycle of an offering (for a product or service) and owns the strategy and execution for bringing that offer to market. You can read this article about a day in the life of an offering manager at IBM 👉 ibm.co/3CfytBe 🙂
![SAFEPLANET - ดาวเคราะห์ [ THE PLANET ]](http://i.ytimg.com/vi/4X1XL3I_k3c/mqdefault.jpg)
Out of the many videos for GPU/CPU, this video saved my time as well as loved the simplified story. Thanks Alex & IBM
IBM dev rels are the best when it comes to explaining stuff...
Facts
Fax mon
Agreed 🤝
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?
"Gaming is no longer the focus of GPUs anymore"!
Thanks guys
Lmao I paused the video just to check on this statement.
No mention of ⛏
What do you think now?
True then, very very true now
Finally a more layman's terms video on the subject, thanks!
I was a layman then I took and arrow to the knee to become a Standingman who can use complex terminology
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.
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 it’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.
Can we all just take a second to appreciate how easy this woman makes writing reversed look?
She doesn't even bat an eye!
Don't you think that it's much more likely that they simply mirrored the video along the vertical axis?
I think so, because it's much more likely that she's right-handed instead of left-handed.
BRAINZ
All these IBM explanation videos are made that way. It's a simple horizontal flip.
......
My thoughts exactly
@@47Mortuus wooooosh
I love IBM, I'm holding the IBM Certified Cyber Security Analyst Professional Certificate and the experience was awesome throughout the 8 coursed
Having an exam in 2 hours time and I'm here to know a killer explanation of a GPU. Thanks for this.
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
Well actually we don't write backward. Here is a blog post we wrote that explains how we do it, with a photo. ibm.co/2LTPMjo
@@IBMTechnology that link doesn't work :(
(at least from mobile)
She writes it the regular way and the video itself is mirrored.
Lol leads me to channel called "post" but nothing is posted.
I think they basically invert the video after shooting.
I study it and nowhere I found this good videos, IBM is awesome
Wow, I had a very vague (and wrong, lol) idea of what a GPU was. It actually makes sense for me now.
The best and easy to understand explanation so far. Thanks!
We're glad you found it useful, Kiran! 🙂
Amazing explanation. Thank you so much for bringing in the clarity on CPU vs GPU.
I've been looking for a good video
And finally I found the best one
Thanks a lot 💓
GPU are more than gaming, inally people now days realised .thanks for making it easy to understand IBM and Alex.
You're welcome, thanks for watching! 🙏
Most of this lectures seen left handed which indicates it horizontally flipped videos... *Cracked*
Wow - I can't begin to tell you how enlightening this short video was. It has, in 8mins, shed great light onto two MSc modules I'm working through right now: Blockchain (PoW mining) and Cloud Systems. I came for the blockchain mining but stayed for the relevance to cloud and virtualizaiton. 5 *s.
Writing backwards in real time whilst multi tasking and multi processing is seriously impressive
She is a human GPU :3
it's just an horizontal reflected video.
@@porrasbrand good call.
@@Lights_Darksthere are 2 glass
I almost thought she wasn't human.
That's cool how you write backwards so neat
Great presentation and clear explanation to get basics of the GPUs etc... make sense in a simple manner.. i m loving the IBM Technology videos ...
Thanks a lot mam for this video. It has been explained nicely.
Thank you ma'am for clearing up this run away computer technology components n its effects on user.
Thanks very much for simplifying. This helps a lot.
In summary, GPUs are focused on matrix computations in order to create images.
CPUs execute more general and more complex instructions.
A CPU is like a musician that can read and write music.
A GPU is like a musician that knows specific chords.
This is the coolest white board i've ever seen!
Ok but my question is how in the God's good world she's writing in reverse so smoothly and explaining alongside
See ibm.biz/write-backwards for details
i love the way she says virtual desktop infrastructure
i recently looked at a brand new cpu, they are a fasinating piece of kit!
Good speech presentation, good visual presentation with the colored markers & screen layout. I am impressed!
And I as well!
Great video, more impressive how well she writes backwards.
lol
The video is horizontally flipped. She is writing normally
Simple, but effective. The drawings help a lot. Thank you!
You are most welcome.
draw , write backwards. . .
wow
i subscribed, and liked already
LOL I noticed that too.
Amh, described this way, GPUs include also iGPUs (rightly). So, Intel are the biggest producer of GPUs.
People are trippin! Certainly not a bad video, but far from best. Everything can be summed up in less than 2 lines why 7 min!: GPU's have more cores than CPU and are thus able to handle compute intensive tasks. You can choose to have your own gpu infrastructure, or pay cloud-based resources. To call this a stellar explanation of GPU's is simply not acceptable! I have said my piece
sharp , neat and informative
This is a great introduction
Excellent presentation...many thanks! HAL would approve :-)
Why gpus don't replace cpus ? Why do we need both ? What does the cpu that the gpu can't ?
Excellent
Did she just write backwards that whole time??
I think it's more of edit
Flip each frame horizontally
Can you elaborate cuz i Cant wrap my head around it @@Thanos-hp1mw
It's mirror bro
You Rock! Alex
Good intro video, but why did IBM not invest in the GPU industry?
Great explanation 👏🏿
Good Explanation. Nice Job
Hey Alex! Looks like you are doing very well since your days in Troy. Of course, I'm not surprised. Keep up the amazing work!
I admire the way you can write things behind the glass like that. I tried and it's so HARD!!
she never actually wrote backwards they just flipped the video around in post production
Well actually we don't write backward. Here is a blog post we wrote that explains how we do it, with a photo. ibm.co/2LTPMjo
Tremendously Helpful Thx!
Exellent lecture! Thank’s a lot ma’am
so comprehensive,
thanks
Amazing video.
Thank you for your good explain. May be, I can understtand the defference between CPU & GPU.
But I have more question. from your direction ,Writing the keywords was very difficult?
Not an explanation of what a GPU is, but its uses.
excellent job by the speaker!
Even a basic computer need GPU.
yeah technology are becoming so advanced that a gpu from 2017 is considered obsolete already but a car from 2017 is still considered new lol.
Maria Sharapova explaining computers
Speechless
Excellent.
Got to load off this question off my mind: Why don't we just have a cpu that has the capability of gpu and cpu at the same time? Like a god processor or something
But if GPUs are so massive more powerful why not switch everything to them & go completely parallel processing for all applications
Well..this explains what i needed, thanks
If a GPU is so great at everything then why is it not used in place of a CPU.
Is it because the OS is stuck with some architecture that only works with a CPU or cpu brands (Intel / amd) or is there some other reason.
Hi @indrajeet500 thanks for reaching out. GPUs have the capability of processing particular applications far faster than CPUs, but GPUs lack the some of the core functionality of CPUs which are needed for modern operating systems. GPUs are most suited for intensive compute applications such as low-latency graphics and deep learning, whereas CPUs are built for everyday computing. For now, GPUs and CPUs are a robust team!--Alex
In my learning from what I understand and how I explain it to people in a cliff notes version. Is that the CPU is quicker at writing out the equation, the GPU is quicker at coming up with the answer. I know it is a little thin but it seems to fit the description.
@@IBMTechnology can you tell us more about the core functions that cpus can do it but gpus can't ?
Technically, when you make an operating system, everything must executed in order. You can't do that in GPU because it's parallel processor. Therefore, you need serial processor (in this case CPU)
@@neamam9228 complex arithmetic calculations, GPU are best for simple calculations that are computationally intensive such as graph traversal, encryption and decryption
what is vram and what is does to gpu and which one matter the most gpu or vram?
Hi Alex!
Good video , but I wanted to know that laptop with small cpu and beast GPU good?
3:44 “[AI] is something that a CPU cannot do on its own.” That’s not off the wall but not really true. I ran mistral 7b with cpu using hugging face. If I get it from source, I do need NVIDIA gpus based on the way the code is set up. You can do a lot of great AI on CPU though.
Great video on clarification!
...Also are we NOT going to address the fact that the presenter has been writing in REVERSE for the purpose of this lesson?
It's flipped in post-production. See ibm.biz/write-backwards for details.
Excellent!
very informative info,, hats off
Brilliant video post
good job
well explained. Like it a lot.
Glad it was clear, Immanuel. Thanks for visiting.
Great thank you
Great info, and also such a cool presentation setup.
This is more B2B ad for cloud compute gpu than education on gpu's.
Thanks
Explained well, thank you.
Thank you. That was great explanation. Do you have a video with data that shows the speed differences of CPUs and GPUs or a CPU w/out a GPU? Thanks
Hi Julius! At this time that kind of content does not exist, but it is something we are working on for future videos.
Good video... although...
It needs just a 'minor' correction---
CPU's can have only 1 core... the cores run in Parallel (not serie)
the core in the GPU usually run in slower speed than the CPU cores...
(there are a number of technical reasons for this limitation...)
the big difference is that the specialization
the GPU was initially developed for a specific task (as the name states)
and as the goal was mainly graphics calculation (although it can be used for others... now AI, ML, ...)
it has a small and specific set very math-oriented...
It shines in any task where there are the possibility of using a distributed load
(a bunch of simple tasks, remember these are simplistic cores)
that can tun in parallel and spread the load for the GPU...
;-)
your first paragraph is exactly what i was thinking, thanks for additional info too.
I agree that mistakes were made, but it's not right to say _"CPUs can have only 1 core... the cores run in parallel"._ As she said, a CPU can have one or many cores, but usually much less than the GPU. Also, the parallel vs series argument is quite strange. The OS manages multithreading which can mean that a program can run in parallel on a CPU. The same is true for a GPU (This is where I disagree with the lady in the video). But I agree with her in saying that GPUs are specifically designed and suited to tasks that run in parallel, while CPUs can do both well.
Good comment! it makes me clear the point that if GPU is fast why we need CPU, the main difference is that GPU's core is simplistic cores, doing specific tasks and running at a slower speed than the CPU.
Are both necessary for a gaming pc? If so what brand and capacity do you recommend?
yeah both are quite necessary id say just type your budget and a pc build related to that should show up
How does the app code know what to transfer to the gpu or the cpu
thanks for knowledge information keep sharing good for humanity love and respect from pakistan
Informative video
Wether it's true or not; considering GPUs as overpowered CPUs is a little bit disappointing.
subed! great content! love!
Top presentation
Great explanation
..so how to choose the optimum gpu for an existing cpu?
Sooo cool video! Thx
good video thanks
If I understood correctly GPU have much more computing power so why using CPUs at all? beacuse they are cheaper?
Does IBM offer training for reverse writing?
you can write entire Unicode on base
More of an advert for compute services than an explanation of GPUs.
Offload of graphics video rendering is certainly a thing but construction was a poor example, nobody live renders the CADD model, it wouldn't even be legal in many cases for permitting and engineering certification reasons, they used fixed plans that have been hashed and recorded and any field changed are appended. The laptop has plenty of GPU to display the approved fixed graphics.
thank u
I need a book where i can aboard tecnical details? anyone any book?
I love learning with her.
Good Presentation
Thank you!
What is offering manager?
Hi Tom! An Offering Manager is responsible for the full lifecycle of an offering (for a product or service) and owns the strategy and execution for bringing that offer to market.
You can read this article about a day in the life of an offering manager at IBM 👉 ibm.co/3CfytBe 🙂