Very clear video thank you. Basically Amdahl's Law is an equation that outputs a sort of ratio that tells you how much gain you get from incorporating parallelization with n cores. So the output answer would read something like "you get 1.2x speedup" or whatever calculation it takes to get there
Prof. Dr. Juurlink, thank you so much for your informative and crisp videos! They are very helpful for my computer architecture course here in the U.S.!
Serial vs parallel is basically what effects everything not just chip logic. There u can see how more serial based CPU cores cannot scale as good as multi parallel GPUs. It’s all coming back to basics of processing where some tasks must be performed in series and others can be heavily parallelized. That sweet spot between them is constantly being challenged and pushed to achieve best possible results. In my opinion level of true parallelization and processing optimization will only increase also due to slowdowns and limits of chip shrinking. Golden years of just adding more smaller transistors and increasing clock speed r over even they will still play an important role, but surely as not as important as they played in the past.
4:05 I think I became colorblind
Best explanation on internet! will never forget Amdahl's law
Very clear video thank you. Basically Amdahl's Law is an equation that outputs a sort of ratio that tells you how much gain you get from incorporating parallelization with n cores. So the output answer would read something like "you get 1.2x speedup" or whatever calculation it takes to get there
Why did I find this course so late? Thank youuuuu! :D
Prof. Dr. Juurlink,
thank you so much for your informative and crisp videos! They are very helpful for my computer architecture course here in the U.S.!
Thanks but the echo makes it barely understandable.
Serial vs parallel is basically what effects everything not just chip logic. There u can see how more serial based CPU cores cannot scale as good as multi parallel GPUs. It’s all coming back to basics of processing where some tasks must be performed in series and others can be heavily parallelized. That sweet spot between them is constantly being challenged and pushed to achieve best possible results. In my opinion level of true parallelization and processing optimization will only increase also due to slowdowns and limits of chip shrinking. Golden years of just adding more smaller transistors and increasing clock speed r over even they will still play an important role, but surely as not as important as they played in the past.
thanks for putting this video out. very helpful!
great video ... ez to follow and understand... what a goat
Dankeschön!
oh brilliant video !!
Thank you ..!
great video
Great explanation. Thanks!
thats great
Totally lost me from 3 minutes.