data classification hardware acceleration · 2013-10-07 · using of hardware acceleration page 14...
TRANSCRIPT
Data Classification Hardware Acceleration
Ivan Manuylov Senior Software Developer, DLP Research
Kaspersky Lab
Speed
PAGE 2
Speed
PAGE 3
Speed?
PAGE 4
Speed?
PAGE 5
Speed?
PAGE 6
Speed?
PAGE 7
Hardware
Cores
PAGE 9
Who has access to 1000+ cores?
Purpose of GPU
PAGE 10
General Purpose computation on GPU
How to use GPGPU
PAGE 11
Direct Compute
Cross platform
Multi vendor
C kernel
Languages:
C/C++
.NET
Java
Ruby
Python
Windows
Multi vendor
HLSL kernel
Languages:
C++
C++ AMP
.NET
Cross platform
NVIDIA
C/C++ kernel
Languages:
C/C++
.NET
Java
Fortran
Perl
Python
Kernel code
PAGE 12
Using of Hardware Acceleration
Using of Hardware Acceleration
PAGE 14
Research
Hardware
PAGE 16
CPU
Intel Core i5 – 750
2.66 GHz
4 cores
DDR3:
667 MHz
12 Gb/s
GPU
NVIDIA GeForce GTS 450
1.6 GHz
192 cores
GDDR5:
1.8 GHz
58 Gb/s
Fingerprinting
Fingerprinting
PAGE 18
Fingerprinting
PAGE 19
100 Kb
100 000 hashes
Fingerprinting
PAGE 20
2x faster
0
200
400
600
800
1000
1200
1400
1600
1800
0 5 10 15 20 25
µs
Kb
CPU
GPU
2x
Fingerprinting
PAGE 21
CPU
is
better
GPU
is
better
Keywords
Keywords
PAGE 23
Keywords
PAGE 24
What is the performance boost?
Keywords
PAGE 25
10+ times
What is the performance boost?
Keywords
PAGE 26
0
10000
20000
30000
40000
50000
60000
0 10 20 30 40 50 60 70
µs
Kb
1000 keywords
CPU
GPU10X
GPU
is
better
Epilogue
Summary
PAGE 28
Fingerprints search 2x
Keywords search 10x
We can do it!
PAGE 29
Data Classification Hardware Acceleration
Thank you!
Ivan Manuylov
Senior Software Developer, DLP Research,
Kaspersky Lab