I Don't Want to Live On This Planet Anymore: Epyc, Find Us a New One

i don't want to live on this planet anymore and you know mars mars is not exactly inviting looking is it really possible that there are no other readily habitable globes in the heavens surely there's one out there somewhere for every grain of sand on earth's beaches there's at least 10 stars in the universe and you figure there's at least one planet on average around those stars if not more so there's going to be more planets than stars surely there's got to be something out there somewhere an extra solar earth so where are all those planets we we need to find them scientists are developing new techniques to find these extra solar planets all the time i mean we've got a lot of data we just don't know how to reliably find extra solar earths in the data that we have it's a tricky problem one technique involved the development of a coronagraph which revealed four jupiter-sized planets orbiting a star now this took almost a decade of observations we don't we don't have that kind of time another method is called the transit method basically what this does is it looks for a star and then it looks for the star to periodically dim and based on how much it dims and how often it dims you can sort of figure out how big the planet is you know sort of where it is and the really cool thing about this technique is that you can use imaging arrays and image a bunch of stars all at once just take a ton of observations you can do thousands or tens of thousands of stars whatever you can fit in a field of view so this lends itself to uh numerical analysis data analysis big data analytics or whatever you want to call it in order to find extra solar earths the problem though is that earth isn't really that big so the amount of dimming that you'll see from a planet's size to earth yeah you know stars are analog critters they're going to dim and brighten on their own enter the lowell observatory the lowell observatory is an independent non-profit research institution founded in 1894 by boston mathematician percival lowell it's near flagstaff arizona scientists at lowell university and yale university have built something they call the extreme precision spectrograph this is one of the first instruments where scientists actually expected to have the level of precision necessary to locate extrasolar earths that meet the criteria and that uh you know are not super gas giants or anything like that but have a pretty dramatic local dimming effect now at the lowell observatory they're already collecting reams and reams and reams of data in fact they're having a little bit of a data overrun issue it turns out if you can't process a day's worth of information in less than a day typically way less than a day pretty soon you're going to be overrun with data you're going to be drowning in data the data really needs to be processed quickly and also distributed to other research scientists around the world yale university they're not just sitting around they need that process data in order to do their analysis and research data overruns a giant mess of data drowning in data sounds like they could use a computer janitor so i've been talking to dr joe lama about precisely what sort of computer janitorial services they require because i am at their disposal so while astronomers are looking for planets around other stars at night we still need a good model for how stars behave i mean searching for an earth-like exoplanet around you know a star like our sun definitely needle and haystack territory so if we had a better model of our sun it might help us do that so this instrumentation is used during the day and at night for collecting different kinds of data dr lama is running the experiment for the solar collection aspect of it and nasa has already collected 2.8 petabytes of information so the hope is that this massive volume of information might be just the the first chapter of an epic tale about human space exploration and finding the first habitable exoplanet i got a plan but i gotta call in some favors [Music] yeah oh yeah yeah yeah yeah well i mean you know it's for a good cause they're a non-profit we could really i mean you know we could really get a lot done oh great thanks that's that's awesome i really appreciate it i'm sure they will too it's uh thank you thank you thank you again good news everybody well i've got a plan and my plan is to process that data as close to real time as possible as soon as the data comes in process it and get an indexed compressed version of the data stored on a high speed storage array something like flash memory now we're going to keep the original data on a spinning rust you know hard drive array that is local to the server so we could quickly pretty quickly load information from that you know mechanical storage because hey 18 terabyte hard drives are a thing and 18 terabyte flash drives are those are expensive so we can reload any data that we need from the local storage array if we need sort of even more storage that'll fit in a single chassis because 200 gigabytes a day doesn't you know even 18 terabytes doesn't last all that long or 18 terabytes times 12 drives we can offload that extra storage for networking and so in addition to storing the information that we process as close to real time as possible probably also going to deploy a couple of containers on the server so that other research scientists can make a request and fill out a web form basically and then be able to get any other information that they need and download it in real time this is probably going to be an ongoing process probably going to end up seeing a couple of videos about this and the other stuff that goes into it so now we [Music] wait wow that was stealth i think it's time for a build [Applause] [Music] [Applause] [Music] do [Music] as their voltron montage implied gigabyte and amd have really contributed generously here we cannot thank them enough without them this project would not have been possible and kiosia also kicked in for some flash storage we're using their cm6 enterprise ssds for our storage array and we've got four of them as configured in this chassis so we're going to be able to process data as close to real time as possible thanks to this flash array the final build has two 32 core epic processors and one terabyte of ram some of you at home have 512 gigabyte ssds this computer has one terabyte of ram now with this hardware we can process a full day's worth of data in much less than a day so we can catch up on all the data that sort of overrun everything else and also be able to really quickly reprocess data whenever they change the algorithm the centerpiece and crown jewel of the plan here is of course the gigabyte g482 this is a research scientist's dream server it's for you you know a lot of the time the data center they're after the most compact machine possible but this chassis is one of the most flexible enterprise chassis that i've ever seen it combines nvme three and a half inch storage there's even two and a half inch sata storage and we've also got all the pci express connectivity that we'd ever need and we don't have an algorithm yet that'll take advantage of gpus or fpgas or anything like that so all of the heavy lifting here is down to amd epic and the 32 core monster cpus that we have in this chassis are going to cut through that data really quickly no problem the 32 core cpu sort of balance high clock speed and uh core density for sort of the sweet spot for this particular algorithm looking for extra solar earths now there's still plenty of room for optimizations in fine tuning in future videos with level one but let's check in with dr lama and find out a little bit more about the lowell observatory his team and the goings on so that we can sort of have fun and live vicariously so i've got dr joe lama here with me hello and welcome you're live from the observatory hi wendell how are you great to see you so uh you know this thing is a lot of horsepower a ridiculous amount of horsepower and you are gathering data almost faster than we can really store it because you know you and i were working together and looking at some stuff and that kind of thing but uh you know walk us through it like what is the deal with this level of data it's absolutely bananas and you're using the telescope during the day yeah i'm doing everything backwards i'm definitely a social hour astronomer not a nighttime astronomer so yeah you know when uh we first started this project we didn't really think too much about you know the computing needs of this it was sort of oh here's a cool idea let's go do it and we'll kind of figure out the details later and in in you know as you well know those things come back and form you uh so but yeah you know we have this one star up during the day the sun uh no none of my colleagues are vying for telescope time they will just want to use the night time so i've got unobstructed access to the telescope all day every day pretty much uh so yeah and as you say that generates a lot of data well i mean it wasn't just you though i mean it was like i was doing some of the prep material for this and nasa and one of the things you sent me is like it's like oh yeah nasa just casually dropped oh yeah we've got like a petabyte of data on the sun during you know daily observation and it's like okay there's something to this oh yeah absolutely so the sun is just you know it's so close by you know all the other stars you see in the night sky are just these point sources and while we can collect a lot of data on them they are still just point sources and there's a lot of things that happen between us and those stars that prevent us getting uh as much data as we can on them so you know stars like the sun it's it's this really cool opportunity to uh to look and just understand what's going on inside these these big fireboys it's really really a cool opportunity yeah i think that uh you know we've already been sort of testing the server a little bit with some data sets and you know running through that and um you know it really is like a like a buzz saw just cutting through the data i mean amd epic and what gigabyte has put together uh in this chassis they really sort of carry it home as far as data processing in real time and like whatever crazy software and algorithms and stuff like that that you guys come up with it really is crazy to think that this might be the machine that finds you know a planet where and it's like oh we need to look more closely at this oh we're getting polarized light from this planet maybe the plants on the planet are absorbing the other polarization of light you know there's it's possible oh my god yeah it's so true um yeah we can't thank gigabyte enough this is way more computing power than we ever thought we'd we'd get access to or maybe we'd even need but uh you know when when someone gives you a hammer you find the nail to hit the problem with so yeah we will throw everything we've got at this machine now i'm really excited you know it's not just the you guys aren't just collecting data for yourselves either in the project i mean you've got a lot of other uh higher education and other researchers that you're feeding the data to so it's not just you know your group this depends on i mean there's there were some pretty big names in there yeah that's right so what we want to do is you know make this data as open as possible so all of my colleagues around the world can you know download it and have a crack at beating this problem we have of trying to tease out the tiny signals from orbiting planets yeah you said um i think on the existing system that when you're running data processing and like you bring up the terminal you would you would type a few things and then like a few seconds later it would sort of go across the screen it's like using dial-up internet that's the thought process i had oh the load average is 150 is that is that good yeah so yeah this this does quite a this this will cut through that with uh uh quite a bit more ease than the uh than the existing setup and we can also scale it so in terms of like making that data accessible and dealing with that on the software side um we're looking at doing that with containers and that is something that we can revisit in a follow-up video i'm sure i'm going to try to make it out there at some point so at some point there's going to be a part two yeah definitely comment below and you know do all the thing and we'll see if we can if we can you know arrange that but i would love to come out there and actually see stuff in person and like let's shred the data let's do the consulting thing and figure it out right you know and it's really cool having such a powerful machine you know it makes you normally when you want to re-analyze something you know you change something in the code and then you have to wait a week to see if what you did works or not and with this system we're not going to have to do that so it's going to you know joking aside it's really going to speed up literally speed up both the data processing but also the analysis it's it's such a it's so cool yeah both sockets are i think you'll be able to do your real-time processing as normal but also when you have an algorithm change that can be running in the background because you know you have months of data and that's still going to take a while to process but it's not going to interfere with the daily processing and this chassis because it's got so much pci express connectivity you can also expand the physical disk storage so you can have inexpensive you know locally attached storage we did our garbage server build and you could use something like that to add another you know 48 three and a half inch base and that'll get you in the petabyte range with some reasonably sized hard drives and that's local attached storage so it's automatically really fast you can do stuff over over the network of course too that's just more interconnects but also fpgas and gpus at some point in the future it's like you you've got to invent the algorithm on the cpus you've got to do the uh the inventing and the hard thinking with general purpose compute you can't do it until you figure out what you need with something specialized like a gpu and that's why these things are so critical to research scientists yeah that's right and you know people my colleagues are starting to develop all these machine learning techniques and all these these cool applications that we can use gpus for so this chassis is gonna it's going to do it all yeah it's it's really is gonna be my one-stop shop i no longer have to buy these really powerful desktops you know i can get like my fancy imac or whatever and zoom into it it's going to be great yeah it'll be able to run all of their jobs as well i mean you know you might have an office award for the person that comes up with the job that actually blocks the server down yeah that's not a bad one we could do that competition i think uh rit guys have joked that i think i've got the single most powerful machine probably in northern arizona maybe so yeah it's gonna be that's gonna be really cool well epic is definitely gonna bring home the bacon there's no doubt about that so i'll it'll be interesting to do the follow-up well uh thank you for coming on it's been awesome any uh parting words of wisdom any anything you want to check out the lowell observatory is linked below and you can check out the research maybe maybe kick him a few bucks yeah a lot of awesome stuff we're a non-profit research organization you know we're doing the best we can in these trying times our tours have just started back up so if you find yourself coming through northern arizona.edu and you can book yourself onto a tour um a huge thank you to you and the guys at gigabyte for making this happen it's it's beyond amazing i'm so thrilled with how it's all worked out oh and amd and keoksia i called in a lot of favors i'm gonna have to land bargaining from you well it's it's pretty easy when you're a non-profit because you can use the magic words tax write-off and then you know all of a sudden all the doors open and and it's sort of magical but yeah you know lol observatory check him out i really love the the work is being done and it is really exciting to think about the next you know uh uh what i always say extrasolar earth but it's uh what do you guys call it we just shortened it to exoplanets oh yeah that's a you know earth-like exoplanet is kind of how we say it in the biz the next earth-like exoplanet could be found by amd epic and this machine that is pretty bananas so it's really awesome to have the opportunity to work on this so thank you for that oh well thank you this has been a great project it's been a ton of fun and this is just the beginning too so i'm looking forward to more of these excellent well once again i want to thank amd and gigabyte for their awesome support on this project i love working with non-profits if you've got something that you want to do you know reach out maybe we can work something out it's been really great special thanks to keoxia for their flash storage array i'm sure this isn't the first time we're going to see this monster beast gigabyte chassis and server videos because it's pretty much the chassis to have in a hyper-converged infrastructure i mean it does everything be sure to check out the lowell observatory check out their mission and maybe kick them a few bucks they are a non-profit after all i'm little this is level one i'm signing out you can find me in the level one forums you

Channel: Level1Techs

Views: 25,842

Rating: 4.9702048 out of 5

Keywords: technology, science, design, ux, computers, hardware, software, programming, level1, l1, level one

Id: ldN7PlUEV0M

Length: 19min 7sec (1147 seconds)

Published: Thu May 27 2021

Reddit Comments

[u/Orcblood17]

I just love Wendell. 😂

[u/fastcashlost]

As yes, Wendell and another exciting adventure in real world bonkers computing. Dual EPYC, 1 TB of RAM, 4 Kioxia flash drives NVMe Gen 4 with 3 DWPD. Sizes available are from 800GB to 12.8TB.

The two major thoughts that crossed my mine are:

1) you need more RAM, BC you always need more RAM.

2) you need WAY WAY more storage BC data always expands to exceed storage capacity and space is the big leagues for data creation.

Pretty close to overkill.

[u/LivingBrick3]

that a interesting title....