Very nice demo. Julia seems to have several different approaches to parallelism, and now there’s FLoop to add to the mix. Is there someplace that summarizes an overall strategy to parallelism for someone learning Julia?
Are there more resources for this? I ran the birthday problem step-by-step with this video. I had to add the StaticVectors and the FLoops (which acted like it wasn't installed, but then updated?). And now my 2018 MacBPro is not as fast when computing anything in Julia. All the things I did, the @SVector and @floop, none of those speed things up and in each case slowed them down. I've Julia in VS Code. I'm happy to try it all again in something else, but it weird that every one of these solutions to speed things up, only slow everything down.
Is the @reduce macro possibly hitting the bottleneck of concurrent access to the histogram? Is there a fix "under the hood" to avoid the potentially negative consequences of this concurrent access?
Hi Alan love this info - take a look at AMD Threadripper CPUs , I'm sporting 32 Threads over 16 CPUs man ! ( also suggest try out NUMA / Gamer mode after BIOS upgrades )
@Molochness yes absolutely 😊 my AMD Threadripper CPU w 16 CPU x 32 Threads running Ubuntu Linux is burning through this Julia computation stuff in nanoseconds - thats right BillionThs of a second ! It's so fast its hard to believe - but yes the answers are correct to 15 Sig Figs !
Please indent the code properly next time. It is actually disturbing to see this. I know it is not mandatory in julia, but it makes it easier to read and understand.
![[08x04] Intro to Julia Multi-Processing (It's not the same as Multi-Threading!)](http://i.ytimg.com/vi/uKdpY6Je6Oc/mqdefault.jpg)
![เปิดบ้าน โคตรสวย ป๋องกพล รู้จักตั้งนาน เพิ่งรู้ว่ารวย!!! l [Nickynachat]](http://i.ytimg.com/vi/tmgCF_2HfYI/mqdefault.jpg)
Pardon me, is there anyone who knows where to buy the jacket of Prof Edelman?
:3 yep
That was my first thought as well
Very nice demo. Julia seems to have several different approaches to parallelism, and now there’s FLoop to add to the mix. Is there someplace that summarizes an overall strategy to parallelism for someone learning Julia?
It will be appreciated ! Especially if there are simple examples of application to distinguish among them.
super helpful walkthrough, thank you!
Are there more resources for this? I ran the birthday problem step-by-step with this video. I had to add the StaticVectors and the FLoops (which acted like it wasn't installed, but then updated?). And now my 2018 MacBPro is not as fast when computing anything in Julia. All the things I did, the @SVector and @floop, none of those speed things up and in each case slowed them down. I've Julia in VS Code. I'm happy to try it all again in something else, but it weird that every one of these solutions to speed things up, only slow everything down.
Is the @reduce macro possibly hitting the bottleneck of concurrent access to the histogram? Is there a fix "under the hood" to avoid the potentially negative consequences of this concurrent access?
Nice Tutorial
How can i download this course completely.for me it shows just week 8 of this course
Hi Alan love this info - take a look at AMD Threadripper CPUs , I'm sporting 32 Threads over 16 CPUs man ! ( also suggest try out NUMA / Gamer mode after BIOS upgrades )
@Molochness yes absolutely 😊 my AMD Threadripper CPU w 16 CPU x 32 Threads running Ubuntu Linux is burning through this Julia computation stuff in nanoseconds - thats right BillionThs of a second ! It's so fast its hard to believe - but yes the answers are correct to 15 Sig Figs !
Please indent the code properly next time. It is actually disturbing to see this. I know it is not mandatory in julia, but it makes it easier to read and understand.
Remember, every indentation you write, is read by thousands of viewers!