SlideShare a Scribd company logo
Hashing
Group A
Indian Institute of Information Technology Vadodara
May 8, 2018
Group A (Indian Institute of Information Technology) Short title May 8, 2018 1 / 23
Overview
1 First Section
Subsection Example
2 Second Section
Group A (Indian Institute of Information Technology) Short title May 8, 2018 2 / 23
Paragraphs of Text
Sed iaculis dapibus gravida. Morbi sed tortor erat, nec interdum arcu. Sed
id lorem lectus. Quisque viverra augue id sem ornare non aliquam nibh
tristique. Aenean in ligula nisl. Nulla sed tellus ipsum. Donec vestibulum
ligula non lorem vulputate fermentum accumsan neque mollis.
Sed diam enim, sagittis nec condimentum sit amet, ullamcorper sit amet
libero. Aliquam vel dui orci, a porta odio. Nullam id suscipit ipsum.
Aenean lobortis commodo sem, ut commodo leo gravida vitae.
Pellentesque vehicula ante iaculis arcu pretium rutrum eget sit amet purus.
Integer ornare nulla quis neque ultrices lobortis. Vestibulum ultrices
tincidunt libero, quis commodo erat ullamcorper id.
Group A (Indian Institute of Information Technology) Short title May 8, 2018 3 / 23
Collision Resolution Technique
Linear Probing.
Quadratic Probing
Double Hashing
Group A (Indian Institute of Information Technology) Short title May 8, 2018 4 / 23
Linear Probing
Linearly probe for the next slot.
LP(K, i) = [hash(K) + i] mod m, ∀i ∈ 0, 1, 2, ..., m − 1
hash(K)= K mod m
K = key, m = size of address space.
i values runs in hash address space.
Example: Keys = 55,98 ,50, 62, 79, 79, 45, 85, 99, 29
Group A (Indian Institute of Information Technology) Short title May 8, 2018 5 / 23
Linear Probing
LP(55,0) = [(55 mod m)+0] mod m =(55 mod 10) mod 10
= 5 mod 10 =5
LP(98,0) = [(98 mod 10)+0] mod 10 = 8 mod 10 = 8
LP(50,0) = 0
LP(62,0) = 2
LP(79,0) = 9
LP(45,0) = 5 (collision 1)
LP(45,1) = 6
LP(85,0) = 5 (collision 2)
LP(85,1) = 6 (collision 3)
LP(85,2) = 7
LP(99,0) = 9 (collision 4)
Group A (Indian Institute of Information Technology) Short title May 8, 2018 6 / 23
Linear Probing
LP(99,0) = 9 (collision 4)
LP(99,1) = 0 (collision 5)
LP(99,2) = 1
LP(29,0) = 9
LP(29,1) = 0 (collision 6)
LP(29,2) = 1 (collision 7)
LP(29,3) = 2 (collision 8)
LP(29,4) = 3
Total collision is 8
Group A (Indian Institute of Information Technology) Short title May 8, 2018 7 / 23
Quadratic Probing
QP(K, i) = [(hash(K) + C1.i + C2.i2)] mod m
C1 = 1, C2 = 1
We look for i2th slot in ith iteration.
Example: Keys = 55,98 ,50, 62, 79, 79, 45, 85, 99, 29
Group A (Indian Institute of Information Technology) Short title May 8, 2018 8 / 23
Quadratic Probing
QP(55,0) = [55 mod 10] =5
QP(98,0) = 8
QP(50,0) = 0
QP(62,0) = 2
QP(79,0) = 9
QP(45,0) = 5 (collision 1)
QP(45,1) = [5 + 1 ∗ 1 + 1 ∗ 12]mod 10 = 7 mod 10 =7
QP(85,0) = 5 (collision 2)
QP(85,1) = [5 + 1 ∗ 1 + 1 ∗ 12]mod 10 = 7 mod 10 =7 (collision 3)
QP(85,2) = [5 + 1 ∗ 2 + 1 ∗ 22]mod 10 = 11 mod 10 =1
Group A (Indian Institute of Information Technology) Short title May 8, 2018 9 / 23
Quadratic Probing
QP(99,0) = 9 (collision 4)
QP(99,1) = [9 + 1 ∗ 1 + 1 ∗ 12]mod 10 = 1
QP(99,2) = 5 (collision 6)
QP(99,3) = 1 (collision 7)
QP(99,4) = 9 (collision 8)
QP(99,5) = 9 (collision 9)
QP(99,6) = 1 (collision 10)
QP(99,7) = 5 (collision 11)
QP(99,8) = 1 (collision 12)
QP(99,9) = 9 (collision 13)
QP(29,0) — (10 collision)
Total Collision 23
Group A (Indian Institute of Information Technology) Short title May 8, 2018 10 / 23
Double Hashing
DH(K, i) = [(hash1(K) + i ∗ hash2(K)] mod m.
∀i ∈ 0, 1, 2, ........m − 1.
hash2(K) =1+[k mod (m-2)]
Group A (Indian Institute of Information Technology) Short title May 8, 2018 11 / 23
Double Hashing
DH(55,0) = [55mod10 + 0 ∗ [1 + (55mod8)] mod 10
[5 + 0 ∗ (1 + 7)]mod 10
5 mod 10 = 5
DH(98,0) = 8
DH(50,0) = 0
DH(62,0) = 2
DH(79,0) = 9
DH(45,0) = 5
DH(45,1) = [5 + 1 ∗ [1 + (45mod8)]]mod10]
(5 + 6) mod 10 =1
DH(85,0) = 5
DH(85,1) = [5 + 1 ∗ [1 + 5]] mod 10 =1
DH(85,2) = 7
Group A (Indian Institute of Information Technology) Short title May 8, 2018 12 / 23
Double Hashing
DH(99,0) = 9
DH(99,1) = 3
DH(29,0) —- 10 collision
Thus total collision =14
Group A (Indian Institute of Information Technology) Short title May 8, 2018 13 / 23
Comparison
Linear probing
Best cache performance.
Suffers from clustering.
Easy to compute.
Quadratic Probing
Cache performance and clustering
Double Hashing
Poor cache performance but no clustering
More computation time because of two hash functions.
Group A (Indian Institute of Information Technology) Short title May 8, 2018 14 / 23
Comparison
Block 1
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Integer lectus nisl,
ultricies in feugiat rutrum, porttitor sit amet augue. Aliquam ut tortor
mauris. Sed volutpat ante purus, quis accumsan dolor.
Block 2
Pellentesque sed tellus purus. Class aptent taciti sociosqu ad litora
torquent per conubia nostra, per inceptos himenaeos. Vestibulum quis
magna at risus dictum tempor eu vitae velit.
Block 3
Suspendisse tincidunt sagittis gravida. Curabitur condimentum, enim sed
venenatis rutrum, ipsum neque consectetur orci, sed blandit justo nisi ac
lacus.
Group A (Indian Institute of Information Technology) Short title May 8, 2018 15 / 23
Multiple Columns
Heading
1 Statement
2 Explanation
3 Example
Lorem ipsum dolor sit amet,
consectetur adipiscing elit. Integer
lectus nisl, ultricies in feugiat rutrum,
porttitor sit amet augue. Aliquam ut
tortor mauris. Sed volutpat ante
purus, quis accumsan dolor.
Group A (Indian Institute of Information Technology) Short title May 8, 2018 16 / 23
Table
Treatments Response 1 Response 2
Treatment 1 0.0003262 0.562
Treatment 2 0.0015681 0.910
Treatment 3 0.0009271 0.296
Table: Table caption
Group A (Indian Institute of Information Technology) Short title May 8, 2018 17 / 23
Theorem
Theorem (Mass–energy equivalence)
E = mc2
Group A (Indian Institute of Information Technology) Short title May 8, 2018 18 / 23
Verbatim
Example (Theorem Slide Code)
begin{frame}
frametitle{Theorem}
begin{theorem}[Mass--energy equivalence]
$E = mc^2$
end{theorem}
end{frame}
Group A (Indian Institute of Information Technology) Short title May 8, 2018 19 / 23
Figure
Uncomment the code on this slide to include your own image from the
same directory as the template .TeX file.
Group A (Indian Institute of Information Technology) Short title May 8, 2018 20 / 23
Citation
An example of the cite command to cite within the presentation:
This statement requires citation [Smith, 2012].
Group A (Indian Institute of Information Technology) Short title May 8, 2018 21 / 23
References
John Smith (2012)
Title of the publication
Journal Name 12(3), 45 – 678.
Group A (Indian Institute of Information Technology) Short title May 8, 2018 22 / 23
The End
Group A (Indian Institute of Information Technology) Short title May 8, 2018 23 / 23

More Related Content

Similar to presentation_n.pdf

Chap 8. Optimization for training deep models
Chap 8. Optimization for training deep modelsChap 8. Optimization for training deep models
Chap 8. Optimization for training deep models
Young-Geun Choi
 
(2020.01) 機械学習による化学反応の予測と設計
(2020.01) 機械学習による化学反応の予測と設計(2020.01) 機械学習による化学反応の予測と設計
(2020.01) 機械学習による化学反応の予測と設計
Ichigaku Takigawa
 
Boetticher Presentation Promise 2008v2
Boetticher Presentation Promise 2008v2Boetticher Presentation Promise 2008v2
Boetticher Presentation Promise 2008v2
gregoryg
 
Ijarcet vol-2-issue-3-904-915
Ijarcet vol-2-issue-3-904-915Ijarcet vol-2-issue-3-904-915
Ijarcet vol-2-issue-3-904-915
Editor IJARCET
 
A Program for Multiple Sequence Alignment by Star Alignment
A Program for Multiple Sequence Alignment by Star AlignmentA Program for Multiple Sequence Alignment by Star Alignment
A Program for Multiple Sequence Alignment by Star Alignment
EECJOURNAL
 
IRJET- Matrix Multiplication using Strassen’s Method
IRJET-  	  Matrix Multiplication using Strassen’s MethodIRJET-  	  Matrix Multiplication using Strassen’s Method
IRJET- Matrix Multiplication using Strassen’s Method
IRJET Journal
 
Performance Analysis of Genetic Algorithm as a Stochastic Optimization Tool i...
Performance Analysis of Genetic Algorithm as a Stochastic Optimization Tool i...Performance Analysis of Genetic Algorithm as a Stochastic Optimization Tool i...
Performance Analysis of Genetic Algorithm as a Stochastic Optimization Tool i...
paperpublications3
 
Super SBM and GM 1,1 Model Approaches for Global Automobile
Super SBM and GM 1,1 Model Approaches for Global AutomobileSuper SBM and GM 1,1 Model Approaches for Global Automobile
Super SBM and GM 1,1 Model Approaches for Global Automobile
ijtsrd
 
SAT based planning for multiagent systems
SAT based planning for multiagent systemsSAT based planning for multiagent systems
SAT based planning for multiagent systems
Ravi Kuril
 
AI4quant 2018 PIXNET Hackathon
AI4quant 2018 PIXNET HackathonAI4quant 2018 PIXNET Hackathon
AI4quant 2018 PIXNET Hackathon
Tzu-Cheng(Jason) Chuang
 
Decision Tree Algorithm Implementation Using Educational Data
Decision Tree Algorithm Implementation  Using Educational DataDecision Tree Algorithm Implementation  Using Educational Data
Decision Tree Algorithm Implementation Using Educational Data
ijcax
 
Decision Tree Algorithm Implementation Using Educational Data
Decision Tree Algorithm Implementation  Using Educational Data Decision Tree Algorithm Implementation  Using Educational Data
Decision Tree Algorithm Implementation Using Educational Data
ijcax
 
Decision Tree Algorithm Implementation Using Educational Data
Decision Tree Algorithm Implementation  Using Educational DataDecision Tree Algorithm Implementation  Using Educational Data
Decision Tree Algorithm Implementation Using Educational Data
ijcax
 
Decision Tree Algorithm Implementation Using Educational Data
Decision Tree Algorithm Implementation  Using Educational Data Decision Tree Algorithm Implementation  Using Educational Data
Decision Tree Algorithm Implementation Using Educational Data
ijcax
 
Multi-Armed Bandit and Applications
Multi-Armed Bandit and ApplicationsMulti-Armed Bandit and Applications
Multi-Armed Bandit and Applications
Sangwoo Mo
 
Genetic Algorithm for solving Dynamic Supply Chain Problem
Genetic Algorithm for solving Dynamic Supply Chain Problem  Genetic Algorithm for solving Dynamic Supply Chain Problem
Genetic Algorithm for solving Dynamic Supply Chain Problem
AI Publications
 
06slide.ppt
06slide.ppt06slide.ppt
06slide.ppt
RohitNukte
 
Stochastic optimization from mirror descent to recent algorithms
Stochastic optimization from mirror descent to recent algorithmsStochastic optimization from mirror descent to recent algorithms
Stochastic optimization from mirror descent to recent algorithms
Seonho Park
 
A prospect theory model of route choice with context dependent reference points
A prospect theory model of route choice with context dependent reference pointsA prospect theory model of route choice with context dependent reference points
A prospect theory model of route choice with context dependent reference points
Pablo Guarda
 
Metric-learn, a Scikit-learn compatible package
Metric-learn, a Scikit-learn compatible packageMetric-learn, a Scikit-learn compatible package
Metric-learn, a Scikit-learn compatible package
William de Vazelhes
 

Similar to presentation_n.pdf (20)

Chap 8. Optimization for training deep models
Chap 8. Optimization for training deep modelsChap 8. Optimization for training deep models
Chap 8. Optimization for training deep models
 
(2020.01) 機械学習による化学反応の予測と設計
(2020.01) 機械学習による化学反応の予測と設計(2020.01) 機械学習による化学反応の予測と設計
(2020.01) 機械学習による化学反応の予測と設計
 
Boetticher Presentation Promise 2008v2
Boetticher Presentation Promise 2008v2Boetticher Presentation Promise 2008v2
Boetticher Presentation Promise 2008v2
 
Ijarcet vol-2-issue-3-904-915
Ijarcet vol-2-issue-3-904-915Ijarcet vol-2-issue-3-904-915
Ijarcet vol-2-issue-3-904-915
 
A Program for Multiple Sequence Alignment by Star Alignment
A Program for Multiple Sequence Alignment by Star AlignmentA Program for Multiple Sequence Alignment by Star Alignment
A Program for Multiple Sequence Alignment by Star Alignment
 
IRJET- Matrix Multiplication using Strassen’s Method
IRJET-  	  Matrix Multiplication using Strassen’s MethodIRJET-  	  Matrix Multiplication using Strassen’s Method
IRJET- Matrix Multiplication using Strassen’s Method
 
Performance Analysis of Genetic Algorithm as a Stochastic Optimization Tool i...
Performance Analysis of Genetic Algorithm as a Stochastic Optimization Tool i...Performance Analysis of Genetic Algorithm as a Stochastic Optimization Tool i...
Performance Analysis of Genetic Algorithm as a Stochastic Optimization Tool i...
 
Super SBM and GM 1,1 Model Approaches for Global Automobile
Super SBM and GM 1,1 Model Approaches for Global AutomobileSuper SBM and GM 1,1 Model Approaches for Global Automobile
Super SBM and GM 1,1 Model Approaches for Global Automobile
 
SAT based planning for multiagent systems
SAT based planning for multiagent systemsSAT based planning for multiagent systems
SAT based planning for multiagent systems
 
AI4quant 2018 PIXNET Hackathon
AI4quant 2018 PIXNET HackathonAI4quant 2018 PIXNET Hackathon
AI4quant 2018 PIXNET Hackathon
 
Decision Tree Algorithm Implementation Using Educational Data
Decision Tree Algorithm Implementation  Using Educational DataDecision Tree Algorithm Implementation  Using Educational Data
Decision Tree Algorithm Implementation Using Educational Data
 
Decision Tree Algorithm Implementation Using Educational Data
Decision Tree Algorithm Implementation  Using Educational Data Decision Tree Algorithm Implementation  Using Educational Data
Decision Tree Algorithm Implementation Using Educational Data
 
Decision Tree Algorithm Implementation Using Educational Data
Decision Tree Algorithm Implementation  Using Educational DataDecision Tree Algorithm Implementation  Using Educational Data
Decision Tree Algorithm Implementation Using Educational Data
 
Decision Tree Algorithm Implementation Using Educational Data
Decision Tree Algorithm Implementation  Using Educational Data Decision Tree Algorithm Implementation  Using Educational Data
Decision Tree Algorithm Implementation Using Educational Data
 
Multi-Armed Bandit and Applications
Multi-Armed Bandit and ApplicationsMulti-Armed Bandit and Applications
Multi-Armed Bandit and Applications
 
Genetic Algorithm for solving Dynamic Supply Chain Problem
Genetic Algorithm for solving Dynamic Supply Chain Problem  Genetic Algorithm for solving Dynamic Supply Chain Problem
Genetic Algorithm for solving Dynamic Supply Chain Problem
 
06slide.ppt
06slide.ppt06slide.ppt
06slide.ppt
 
Stochastic optimization from mirror descent to recent algorithms
Stochastic optimization from mirror descent to recent algorithmsStochastic optimization from mirror descent to recent algorithms
Stochastic optimization from mirror descent to recent algorithms
 
A prospect theory model of route choice with context dependent reference points
A prospect theory model of route choice with context dependent reference pointsA prospect theory model of route choice with context dependent reference points
A prospect theory model of route choice with context dependent reference points
 
Metric-learn, a Scikit-learn compatible package
Metric-learn, a Scikit-learn compatible packageMetric-learn, a Scikit-learn compatible package
Metric-learn, a Scikit-learn compatible package
 

Recently uploaded

Textile Chemical Processing and Dyeing.pdf
Textile Chemical Processing and Dyeing.pdfTextile Chemical Processing and Dyeing.pdf
Textile Chemical Processing and Dyeing.pdf
NazakatAliKhoso2
 
学校原版美国波士顿大学毕业证学历学位证书原版一模一样
学校原版美国波士顿大学毕业证学历学位证书原版一模一样学校原版美国波士顿大学毕业证学历学位证书原版一模一样
学校原版美国波士顿大学毕业证学历学位证书原版一模一样
171ticu
 
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.pptUnit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
KrishnaveniKrishnara1
 
Engine Lubrication performance System.pdf
Engine Lubrication performance System.pdfEngine Lubrication performance System.pdf
Engine Lubrication performance System.pdf
mamamaam477
 
ISPM 15 Heat Treated Wood Stamps and why your shipping must have one
ISPM 15 Heat Treated Wood Stamps and why your shipping must have oneISPM 15 Heat Treated Wood Stamps and why your shipping must have one
ISPM 15 Heat Treated Wood Stamps and why your shipping must have one
Las Vegas Warehouse
 
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesHarnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Christina Lin
 
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
Yasser Mahgoub
 
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptxManufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
Madan Karki
 
Properties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptxProperties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptx
MDSABBIROJJAMANPAYEL
 
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURSCompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
RamonNovais6
 
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
ecqow
 
Understanding Inductive Bias in Machine Learning
Understanding Inductive Bias in Machine LearningUnderstanding Inductive Bias in Machine Learning
Understanding Inductive Bias in Machine Learning
SUTEJAS
 
ML Based Model for NIDS MSc Updated Presentation.v2.pptx
ML Based Model for NIDS MSc Updated Presentation.v2.pptxML Based Model for NIDS MSc Updated Presentation.v2.pptx
ML Based Model for NIDS MSc Updated Presentation.v2.pptx
JamalHussainArman
 
Generative AI leverages algorithms to create various forms of content
Generative AI leverages algorithms to create various forms of contentGenerative AI leverages algorithms to create various forms of content
Generative AI leverages algorithms to create various forms of content
Hitesh Mohapatra
 
UNLOCKING HEALTHCARE 4.0: NAVIGATING CRITICAL SUCCESS FACTORS FOR EFFECTIVE I...
UNLOCKING HEALTHCARE 4.0: NAVIGATING CRITICAL SUCCESS FACTORS FOR EFFECTIVE I...UNLOCKING HEALTHCARE 4.0: NAVIGATING CRITICAL SUCCESS FACTORS FOR EFFECTIVE I...
UNLOCKING HEALTHCARE 4.0: NAVIGATING CRITICAL SUCCESS FACTORS FOR EFFECTIVE I...
amsjournal
 
john krisinger-the science and history of the alcoholic beverage.pptx
john krisinger-the science and history of the alcoholic beverage.pptxjohn krisinger-the science and history of the alcoholic beverage.pptx
john krisinger-the science and history of the alcoholic beverage.pptx
Madan Karki
 
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Sinan KOZAK
 
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
insn4465
 
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by AnantLLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
Anant Corporation
 
132/33KV substation case study Presentation
132/33KV substation case study Presentation132/33KV substation case study Presentation
132/33KV substation case study Presentation
kandramariana6
 

Recently uploaded (20)

Textile Chemical Processing and Dyeing.pdf
Textile Chemical Processing and Dyeing.pdfTextile Chemical Processing and Dyeing.pdf
Textile Chemical Processing and Dyeing.pdf
 
学校原版美国波士顿大学毕业证学历学位证书原版一模一样
学校原版美国波士顿大学毕业证学历学位证书原版一模一样学校原版美国波士顿大学毕业证学历学位证书原版一模一样
学校原版美国波士顿大学毕业证学历学位证书原版一模一样
 
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.pptUnit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
Unit-III-ELECTROCHEMICAL STORAGE DEVICES.ppt
 
Engine Lubrication performance System.pdf
Engine Lubrication performance System.pdfEngine Lubrication performance System.pdf
Engine Lubrication performance System.pdf
 
ISPM 15 Heat Treated Wood Stamps and why your shipping must have one
ISPM 15 Heat Treated Wood Stamps and why your shipping must have oneISPM 15 Heat Treated Wood Stamps and why your shipping must have one
ISPM 15 Heat Treated Wood Stamps and why your shipping must have one
 
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesHarnessing WebAssembly for Real-time Stateless Streaming Pipelines
Harnessing WebAssembly for Real-time Stateless Streaming Pipelines
 
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
2008 BUILDING CONSTRUCTION Illustrated - Ching Chapter 02 The Building.pdf
 
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptxManufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
 
Properties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptxProperties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptx
 
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURSCompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
CompEx~Manual~1210 (2).pdf COMPEX GAS AND VAPOURS
 
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
一比一原版(CalArts毕业证)加利福尼亚艺术学院毕业证如何办理
 
Understanding Inductive Bias in Machine Learning
Understanding Inductive Bias in Machine LearningUnderstanding Inductive Bias in Machine Learning
Understanding Inductive Bias in Machine Learning
 
ML Based Model for NIDS MSc Updated Presentation.v2.pptx
ML Based Model for NIDS MSc Updated Presentation.v2.pptxML Based Model for NIDS MSc Updated Presentation.v2.pptx
ML Based Model for NIDS MSc Updated Presentation.v2.pptx
 
Generative AI leverages algorithms to create various forms of content
Generative AI leverages algorithms to create various forms of contentGenerative AI leverages algorithms to create various forms of content
Generative AI leverages algorithms to create various forms of content
 
UNLOCKING HEALTHCARE 4.0: NAVIGATING CRITICAL SUCCESS FACTORS FOR EFFECTIVE I...
UNLOCKING HEALTHCARE 4.0: NAVIGATING CRITICAL SUCCESS FACTORS FOR EFFECTIVE I...UNLOCKING HEALTHCARE 4.0: NAVIGATING CRITICAL SUCCESS FACTORS FOR EFFECTIVE I...
UNLOCKING HEALTHCARE 4.0: NAVIGATING CRITICAL SUCCESS FACTORS FOR EFFECTIVE I...
 
john krisinger-the science and history of the alcoholic beverage.pptx
john krisinger-the science and history of the alcoholic beverage.pptxjohn krisinger-the science and history of the alcoholic beverage.pptx
john krisinger-the science and history of the alcoholic beverage.pptx
 
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024
 
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
哪里办理(csu毕业证书)查尔斯特大学毕业证硕士学历原版一模一样
 
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by AnantLLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
LLM Fine Tuning with QLoRA Cassandra Lunch 4, presented by Anant
 
132/33KV substation case study Presentation
132/33KV substation case study Presentation132/33KV substation case study Presentation
132/33KV substation case study Presentation
 

presentation_n.pdf

  • 1. Hashing Group A Indian Institute of Information Technology Vadodara May 8, 2018 Group A (Indian Institute of Information Technology) Short title May 8, 2018 1 / 23
  • 2. Overview 1 First Section Subsection Example 2 Second Section Group A (Indian Institute of Information Technology) Short title May 8, 2018 2 / 23
  • 3. Paragraphs of Text Sed iaculis dapibus gravida. Morbi sed tortor erat, nec interdum arcu. Sed id lorem lectus. Quisque viverra augue id sem ornare non aliquam nibh tristique. Aenean in ligula nisl. Nulla sed tellus ipsum. Donec vestibulum ligula non lorem vulputate fermentum accumsan neque mollis. Sed diam enim, sagittis nec condimentum sit amet, ullamcorper sit amet libero. Aliquam vel dui orci, a porta odio. Nullam id suscipit ipsum. Aenean lobortis commodo sem, ut commodo leo gravida vitae. Pellentesque vehicula ante iaculis arcu pretium rutrum eget sit amet purus. Integer ornare nulla quis neque ultrices lobortis. Vestibulum ultrices tincidunt libero, quis commodo erat ullamcorper id. Group A (Indian Institute of Information Technology) Short title May 8, 2018 3 / 23
  • 4. Collision Resolution Technique Linear Probing. Quadratic Probing Double Hashing Group A (Indian Institute of Information Technology) Short title May 8, 2018 4 / 23
  • 5. Linear Probing Linearly probe for the next slot. LP(K, i) = [hash(K) + i] mod m, ∀i ∈ 0, 1, 2, ..., m − 1 hash(K)= K mod m K = key, m = size of address space. i values runs in hash address space. Example: Keys = 55,98 ,50, 62, 79, 79, 45, 85, 99, 29 Group A (Indian Institute of Information Technology) Short title May 8, 2018 5 / 23
  • 6. Linear Probing LP(55,0) = [(55 mod m)+0] mod m =(55 mod 10) mod 10 = 5 mod 10 =5 LP(98,0) = [(98 mod 10)+0] mod 10 = 8 mod 10 = 8 LP(50,0) = 0 LP(62,0) = 2 LP(79,0) = 9 LP(45,0) = 5 (collision 1) LP(45,1) = 6 LP(85,0) = 5 (collision 2) LP(85,1) = 6 (collision 3) LP(85,2) = 7 LP(99,0) = 9 (collision 4) Group A (Indian Institute of Information Technology) Short title May 8, 2018 6 / 23
  • 7. Linear Probing LP(99,0) = 9 (collision 4) LP(99,1) = 0 (collision 5) LP(99,2) = 1 LP(29,0) = 9 LP(29,1) = 0 (collision 6) LP(29,2) = 1 (collision 7) LP(29,3) = 2 (collision 8) LP(29,4) = 3 Total collision is 8 Group A (Indian Institute of Information Technology) Short title May 8, 2018 7 / 23
  • 8. Quadratic Probing QP(K, i) = [(hash(K) + C1.i + C2.i2)] mod m C1 = 1, C2 = 1 We look for i2th slot in ith iteration. Example: Keys = 55,98 ,50, 62, 79, 79, 45, 85, 99, 29 Group A (Indian Institute of Information Technology) Short title May 8, 2018 8 / 23
  • 9. Quadratic Probing QP(55,0) = [55 mod 10] =5 QP(98,0) = 8 QP(50,0) = 0 QP(62,0) = 2 QP(79,0) = 9 QP(45,0) = 5 (collision 1) QP(45,1) = [5 + 1 ∗ 1 + 1 ∗ 12]mod 10 = 7 mod 10 =7 QP(85,0) = 5 (collision 2) QP(85,1) = [5 + 1 ∗ 1 + 1 ∗ 12]mod 10 = 7 mod 10 =7 (collision 3) QP(85,2) = [5 + 1 ∗ 2 + 1 ∗ 22]mod 10 = 11 mod 10 =1 Group A (Indian Institute of Information Technology) Short title May 8, 2018 9 / 23
  • 10. Quadratic Probing QP(99,0) = 9 (collision 4) QP(99,1) = [9 + 1 ∗ 1 + 1 ∗ 12]mod 10 = 1 QP(99,2) = 5 (collision 6) QP(99,3) = 1 (collision 7) QP(99,4) = 9 (collision 8) QP(99,5) = 9 (collision 9) QP(99,6) = 1 (collision 10) QP(99,7) = 5 (collision 11) QP(99,8) = 1 (collision 12) QP(99,9) = 9 (collision 13) QP(29,0) — (10 collision) Total Collision 23 Group A (Indian Institute of Information Technology) Short title May 8, 2018 10 / 23
  • 11. Double Hashing DH(K, i) = [(hash1(K) + i ∗ hash2(K)] mod m. ∀i ∈ 0, 1, 2, ........m − 1. hash2(K) =1+[k mod (m-2)] Group A (Indian Institute of Information Technology) Short title May 8, 2018 11 / 23
  • 12. Double Hashing DH(55,0) = [55mod10 + 0 ∗ [1 + (55mod8)] mod 10 [5 + 0 ∗ (1 + 7)]mod 10 5 mod 10 = 5 DH(98,0) = 8 DH(50,0) = 0 DH(62,0) = 2 DH(79,0) = 9 DH(45,0) = 5 DH(45,1) = [5 + 1 ∗ [1 + (45mod8)]]mod10] (5 + 6) mod 10 =1 DH(85,0) = 5 DH(85,1) = [5 + 1 ∗ [1 + 5]] mod 10 =1 DH(85,2) = 7 Group A (Indian Institute of Information Technology) Short title May 8, 2018 12 / 23
  • 13. Double Hashing DH(99,0) = 9 DH(99,1) = 3 DH(29,0) —- 10 collision Thus total collision =14 Group A (Indian Institute of Information Technology) Short title May 8, 2018 13 / 23
  • 14. Comparison Linear probing Best cache performance. Suffers from clustering. Easy to compute. Quadratic Probing Cache performance and clustering Double Hashing Poor cache performance but no clustering More computation time because of two hash functions. Group A (Indian Institute of Information Technology) Short title May 8, 2018 14 / 23
  • 15. Comparison Block 1 Lorem ipsum dolor sit amet, consectetur adipiscing elit. Integer lectus nisl, ultricies in feugiat rutrum, porttitor sit amet augue. Aliquam ut tortor mauris. Sed volutpat ante purus, quis accumsan dolor. Block 2 Pellentesque sed tellus purus. Class aptent taciti sociosqu ad litora torquent per conubia nostra, per inceptos himenaeos. Vestibulum quis magna at risus dictum tempor eu vitae velit. Block 3 Suspendisse tincidunt sagittis gravida. Curabitur condimentum, enim sed venenatis rutrum, ipsum neque consectetur orci, sed blandit justo nisi ac lacus. Group A (Indian Institute of Information Technology) Short title May 8, 2018 15 / 23
  • 16. Multiple Columns Heading 1 Statement 2 Explanation 3 Example Lorem ipsum dolor sit amet, consectetur adipiscing elit. Integer lectus nisl, ultricies in feugiat rutrum, porttitor sit amet augue. Aliquam ut tortor mauris. Sed volutpat ante purus, quis accumsan dolor. Group A (Indian Institute of Information Technology) Short title May 8, 2018 16 / 23
  • 17. Table Treatments Response 1 Response 2 Treatment 1 0.0003262 0.562 Treatment 2 0.0015681 0.910 Treatment 3 0.0009271 0.296 Table: Table caption Group A (Indian Institute of Information Technology) Short title May 8, 2018 17 / 23
  • 18. Theorem Theorem (Mass–energy equivalence) E = mc2 Group A (Indian Institute of Information Technology) Short title May 8, 2018 18 / 23
  • 19. Verbatim Example (Theorem Slide Code) begin{frame} frametitle{Theorem} begin{theorem}[Mass--energy equivalence] $E = mc^2$ end{theorem} end{frame} Group A (Indian Institute of Information Technology) Short title May 8, 2018 19 / 23
  • 20. Figure Uncomment the code on this slide to include your own image from the same directory as the template .TeX file. Group A (Indian Institute of Information Technology) Short title May 8, 2018 20 / 23
  • 21. Citation An example of the cite command to cite within the presentation: This statement requires citation [Smith, 2012]. Group A (Indian Institute of Information Technology) Short title May 8, 2018 21 / 23
  • 22. References John Smith (2012) Title of the publication Journal Name 12(3), 45 – 678. Group A (Indian Institute of Information Technology) Short title May 8, 2018 22 / 23
  • 23. The End Group A (Indian Institute of Information Technology) Short title May 8, 2018 23 / 23