diff options
30 files changed, 115 insertions, 227 deletions
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"build/main.pdf" "main" 1781166244.8519 0 +["pdflatex"] 1781276013.65163 "main.tex" "build/main.pdf" "main" 1781276014.82908 0 "/usr/share/texmf-dist/fonts/enc/dvips/base/8r.enc" 1775415801 4850 80dc9bab7f31fb78a000ccfed0e27cab "" "/usr/share/texmf-dist/fonts/enc/dvips/cm-super/cm-super-t1.enc" 1775415801 2971 def0b6c1f0b107b3b936def894055589 "" "/usr/share/texmf-dist/fonts/map/fontname/texfonts.map" 1775415801 3524 cb3e574dea2d1052e39280babc910dc8 "" @@ -276,17 +276,17 @@ "/usr/share/texmf-dist/web2c/texmf.cnf" 1775415801 43569 fd570f2fa160877d211e859f687312ba "" "/var/lib/texmf/fonts/map/pdftex/updmap/pdftex.map" 1780237389 5385779 47c0c393a77fd4a098bacfd57d66b88a "" "/var/lib/texmf/web2c/pdftex/pdflatex.fmt" 1780237370 2328183 557d2fa5c1c83b5f04dceecc4ca457bf "" - "build/main.aux" 1781166244.66829 4800 4594825ce0baa5ca0ea560ffac938808 "pdflatex" + "build/main.aux" 1781276014.64623 4800 4594825ce0baa5ca0ea560ffac938808 "pdflatex" "build/main.bbl" 1781165905.36641 7385 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\ No newline at end of file diff --git a/notes/VU_BSc_Defense_Slides_Mateusz_Kwiatkowski-20260610-annot-jd.pdf b/notes/VU_BSc_Defense_Slides_Mateusz_Kwiatkowski-20260610-annot-jd.pdf Binary files differdeleted file mode 100644 index 4e51e3d..0000000 --- a/notes/VU_BSc_Defense_Slides_Mateusz_Kwiatkowski-20260610-annot-jd.pdf +++ /dev/null diff --git a/notes/meeting3.txt b/notes/meeting3.txt deleted file mode 100644 index f058da1..0000000 --- a/notes/meeting3.txt +++ /dev/null @@ -1,49 +0,0 @@ -Jesse -- Latex slides are OK! -1 slides is 1 to 2 minutes - 5 to 10 slides can work. -Slide 4: mention the contributions; In the thesis we answer these RQs, for time limitation, we only focus on RQs 1 and 2. For RQ we do a design and then you can ask me about this after the presentation. -You can skip explaining a RQ. -Skip material instead of cramming material. -As you know and as you've seen in the previous presentations today. - -**Mention societal impact at least verbally. In slide 2.** -Avoid audience members thinking ``he forgot that''. -If you are skipping something -- at least mention that you are skipping it. -Or that there is an extra slide explaining this. - -Before slide 4, the audience must know what predictive analytics is and why is it important to have. -In the `Problem Statement` slide, say `What is predictive analytics`, `Why is it crucial`. -Key for you to explain `What is predictive analytics?` - -Digital Twins -- a lot of elements are shifting about, there are a lot of ways to model these things, and there seems to not be a fully functioning digital twin out there. -There does not exist a system that contains the entire feedback loop. -1) Digital Twins are NOT DONE -- they are actively being developed. -2) Part of being developed is they lack crucial features, e.g., predictive analytics -3) Predictive analytics is this and that... -4) This is important because ... - -You may have to remove the table. - -Slide 2 -- the idea of complex / extremely complex is too bad. -The idea might be a bit too high -- throw in some numbers, the scale of modern datacenters. -Put in some number of different number CPU's, or focus on the number of PETAFLOPS (compute steps per second). - -Change the narrative from Moore's law to something else. -Focus more on the fact that the infrastructure is incredibly large. -DO NOT SHOW THE DENNARD's scaling graph. - -``A single CPU is very complex. (Show ARM Architecture of APPLE MAC) Look, in that something there is this bigger thing, and there is this and there is this bigger thing, and how are we going to simulate this big datacenter, that has so many __layers of complexity__``. A single ARM Architecture Image -- ``This is a complex object''. -In datacenters, there are hundreds of thousands of them. -How do we manage this?'' - -Connect motivation to problem statement via societal context. -``We cannot let these systems go down, we CANNOT Experience failures, we cannot experience performance related issues`'' and that bridges to the need of digital twins to be better able to detect and solve issues in this critical infrastructure. -And that also bridges nicely to predictive analytics. -``What if we can solve problems before they actually occur?`` - -You have to be able to explain something well on a graph with dc <-> dt. -Give a strong motivation for predictive analytics. -Give a strong motivation for failures, or that Digital Twins are just IoT sensors without Digital Twinning. - -Slide 4 add animations to show the research questions. -``Take home message'' instead of Discussion. -Add animations -- to the system model for things appearing. diff --git a/script.tex b/script.tex deleted file mode 100644 index e69de29..0000000 --- a/script.tex +++ /dev/null |
