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and in good old days valuable by any so are the service
the new so every other year disorder was twice as fast
as the one that you had before today how was so some not getting as fast as they had been get and
the graph on this uh on the slide is showing good single third
performance as well as number of course course over over the
years as you can see all of them are flat and it means that the times a hard day was providing freely
the performance improvement the is all our hands a this means that's all
for now as more responsibility to sustain the data would performance
in my research i investigate opportunities and take needs to improve all
but improve performance of a particular software system database system
by using c. p. u. resources efficiently so now let's let's let's
first look at how database systems utilise the c. p. resource
a on the slide bigger off on the left hand side shoals c. p. u. position for
database systems as you can see they are only busy at ten percent of the time
the graph on the right hand side on the other hand zooms into
the business cycles and categorise them interested and useful cycles it
you get for three database systems d. b. m. s. a. e. d. b. m. s. b. d. b. m. s. c.
it you can see more than seventy percent of the time c. p. u. cycles are based the stories altogether show that
the system space more than ninety seven percent of the competition capacity in today's modern source
so there are two main reasons for this waste the first one is interference
it interferes happens due to fog reason multiple users sharing the same so resources
uh for different databases interfere with each other when they shapes all resources in
terms of they are resource demand eh computing resource demand kinds commercially
the resistance all located an entire so for a single user and therefore
and utilise the mushy the second reason is hard there's severe mismatch
into this more than processes their memories wireless them uh uh features that
software can exploit database systems however can mention are not beal
to explode all the available part isn't in the process of in today's modern processes
i used to all major hardware mechanism to improve c.
p. u. transition for database systems isolation and perfection
isolation aloe shaving so resources among different databases the
dots offering much from interference whisper fetching
laws part rising dataquest that would otherwise be see lies by the database system
by isolating and highlighting dataquest you can if you can improve c. v. c. p.
u. transition significantly enhance sustained the data would performance for database systems thanks

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Conference program

Welcome address
Andreas Mortensen, Vice President for Research, EPFL
7 June 2018 · 9:49 a.m.
Introduction
Jim Larus, Dean of IC School, EPFL
7 June 2018 · 10 a.m.
The Young Software Engineer’s Guide to Using Formal Methods
K. Rustan M. Leino, Amazon
7 June 2018 · 10:16 a.m.
Safely Disrupting Computer Networks with Software
Katerina Argyraki, EPFL
7 June 2018 · 11:25 a.m.
Short IC Research Presentation 3: kickoff.ai
Lucas Maystre, Victor Kristof, EPFL (LCA)
7 June 2018 · 12:19 p.m.
Short IC Research Presentation 5: CleanM
Stella Giannakopoulo, EPFL (DIAS)
7 June 2018 · 12:25 p.m.
Short IC Research Presentation 7: Datagrowth and application trends
Matthias Olma, EPFL (DIAS)
7 June 2018 · 12:31 p.m.
Short IC Research Presentation 8: Point Cloud, a new source of knowledge
Mirjana Pavlovic, EPFL (DIAS)
7 June 2018 · 12:34 p.m.
Short IC Research Presentation 9: To Click or not to Click?
Mahsa Taziki, EPFL (LPD)
7 June 2018 · 12:37 p.m.
Short IC Research Presentation 10: RaaSS Reliability as a Software Service
Maaz Mohiuddlin, LCA2, IC-EPFL
7 June 2018 · 12:40 p.m.
20s pitch 2: Gamification of Rehabilitation
Arzu Guneysu Ozgur, EPFL (CHILI)
7 June 2018 · 2:21 p.m.
20s pitch 4: Neural Network Guided Expression Transformation
Romain Edelmann, EPFL (LARA)
7 June 2018 · 2:21 p.m.
20s pitch 5: Unified, High Performance Data Cleaning
Stella Giannakopoulo, EPFL (DIAS)
7 June 2018 · 2:21 p.m.
20s pitch 6: Interactive Exploration of Urban Data with GPUs
Eleni Tzirita Zacharatou, EPFL (DIAS)
7 June 2018 · 2:22 p.m.
20s pitch 7: Interactive Data Exploration
Matthias Olma, EPFL (DIAS)
7 June 2018 · 2:22 p.m.
20s pitch 8: Efficient Point Cloud Processing
Mirjana Pavlovic, EPFL (DIAS)
7 June 2018 · 2:23 p.m.
20s pitch 9: To Click or not to Click?
Mahsa Taziki, EPFL (LPD)
7 June 2018 · 2:24 p.m.
20s pitch 10: RaaSS Reliability as a Software Service
Maaz Mohiuddlin, LCA2, IC-EPFL
7 June 2018 · 2:24 p.m.
20s pitch 11: Adversarial Machine Learning in Byzantium
El Mahdi El Mhamdi, EPFL (LPD)
7 June 2018 · 2:24 p.m.

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