This document discusses the implementation of a lock-free queue in C++. It begins with an overview of blocking vs non-blocking behavior and synchronization primitives like mutexes. It then presents the implementation of a single-producer, single-consumer lock-free queue using atomic operations. It shows how push and pop operations are performed concurrently without locking by atomically updating shared queue pointers. It also discusses techniques like helping other threads complete operations to ensure lock-free progress.
딥러닝 중급 - AlexNet과 VggNet (Basic of DCNN : AlexNet and VggNet)Hansol Kang
The document summarizes the basics of Deep Convolutional Neural Networks (DCNNs) including AlexNet and VGGNet. It discusses how AlexNet introduced improvements like ReLU activation and dropout to address overfitting issues. It then focuses on the VGGNet, noting that it achieved good performance through increasing depth using small 3x3 filters and adding convolutional layers. The document shares details of VGGNet configurations ranging from 11 to 19 weight layers and their performance on image classification tasks.
05211201 A D V A N C E D D A T A S T R U C T U R E S A N D A L G O R I...guestd436758
This document contains an exam for a class on Advanced Data Structures and Algorithms. It lists 8 questions that students can choose 5 of to answer. The questions cover topics like classes and objects in C++, inheritance, exception handling, data structures like trees, heaps, and hash tables, and algorithms like sorting, searching trees, minimum spanning trees, and the traveling salesman problem. Students have 3 hours to answer 5 of the 8 questions, which range from coding exercises to explanations of concepts.
Photo-realistic Single Image Super-resolution using a Generative Adversarial ...Hansol Kang
* Ledig, Christian, et al. "Photo-realistic single image super-resolution using a generative adversarial network." Proceedings of the IEEE conference on computer vision and pattern recognition. 2017.
This document contains summaries of solutions to various LeetCode problems in Java. It begins with a 3-sentence summary of the Rotate Array problem and its solutions, followed by shorter 1-sentence summaries of other problems and their solutions, including Evaluate Reverse Polish Notation, Longest Palindromic Substring, Word Break, and more. Dynamic programming and recursion are discussed as approaches for some of the problems.
Bartosz Milewski, “Re-discovering Monads in C++”Platonov Sergey
Once you know what a monad is, you start seeing them everywhere. The std::future library of C++11 was an example of an incomplete design, which stopped short of recognizing the monadic nature of futures. This is now being remedied in C++17, and there are new library additions, like std::expected and the range library, that are much more monad-conscious. I’ll explain what a monad is using copious C++ examples.
Deep Convolutional GANs - meaning of latent spaceHansol Kang
DCGAN은 GAN에 단순히 conv net을 적용했을 뿐만 아니라, latent space에서도 의미를 찾음.
DCGAN 논문 리뷰 및 PyTorch 기반의 구현.
VAE 세미나 이슈 사항에 대한 리뷰.
my github : https://github.com/messy-snail/GAN_PyTorch
[참고]
https://github.com/znxlwm/pytorch-MNIST-CelebA-GAN-DCGAN
https://github.com/taeoh-kim/Pytorch_DCGAN
Radford, Alec, Luke Metz, and Soumith Chintala. "Unsupervised representation learning with deep convolutional generative adversarial networks." arXiv preprint arXiv:1511.06434 (2015).
- The document contains questions for an exam on operating systems and computer architecture. It lists five sections with multiple choice questions in each section covering topics like operating system objectives and functions, real-time operating systems, security issues, and differences between traditional and modern UNIX kernels.
- The exam is worth a total of 100 marks and students must answer five full questions ranging from 4 to 15 marks each. Questions assess understanding of concepts like process states, Linux kernel components, thread implementation, and multiprocessing scheduling approaches.
Story of static code analyzer developmentAndrey Karpov
The document discusses the history and development of static code analyzers. It describes how early tools used regular expressions that were ineffective for complex code analysis. Modern static analyzers overcome these limitations through techniques like type inference, data flow analysis, symbolic execution, and pattern-based analysis. They also leverage method annotations and a mixture of analysis approaches. While machine learning is hyped, static analysis remains very challenging due to the complexity of code and rapid language evolution.
딥러닝 중급 - AlexNet과 VggNet (Basic of DCNN : AlexNet and VggNet)Hansol Kang
The document summarizes the basics of Deep Convolutional Neural Networks (DCNNs) including AlexNet and VGGNet. It discusses how AlexNet introduced improvements like ReLU activation and dropout to address overfitting issues. It then focuses on the VGGNet, noting that it achieved good performance through increasing depth using small 3x3 filters and adding convolutional layers. The document shares details of VGGNet configurations ranging from 11 to 19 weight layers and their performance on image classification tasks.
05211201 A D V A N C E D D A T A S T R U C T U R E S A N D A L G O R I...guestd436758
This document contains an exam for a class on Advanced Data Structures and Algorithms. It lists 8 questions that students can choose 5 of to answer. The questions cover topics like classes and objects in C++, inheritance, exception handling, data structures like trees, heaps, and hash tables, and algorithms like sorting, searching trees, minimum spanning trees, and the traveling salesman problem. Students have 3 hours to answer 5 of the 8 questions, which range from coding exercises to explanations of concepts.
Photo-realistic Single Image Super-resolution using a Generative Adversarial ...Hansol Kang
* Ledig, Christian, et al. "Photo-realistic single image super-resolution using a generative adversarial network." Proceedings of the IEEE conference on computer vision and pattern recognition. 2017.
This document contains summaries of solutions to various LeetCode problems in Java. It begins with a 3-sentence summary of the Rotate Array problem and its solutions, followed by shorter 1-sentence summaries of other problems and their solutions, including Evaluate Reverse Polish Notation, Longest Palindromic Substring, Word Break, and more. Dynamic programming and recursion are discussed as approaches for some of the problems.
Bartosz Milewski, “Re-discovering Monads in C++”Platonov Sergey
Once you know what a monad is, you start seeing them everywhere. The std::future library of C++11 was an example of an incomplete design, which stopped short of recognizing the monadic nature of futures. This is now being remedied in C++17, and there are new library additions, like std::expected and the range library, that are much more monad-conscious. I’ll explain what a monad is using copious C++ examples.
Deep Convolutional GANs - meaning of latent spaceHansol Kang
DCGAN은 GAN에 단순히 conv net을 적용했을 뿐만 아니라, latent space에서도 의미를 찾음.
DCGAN 논문 리뷰 및 PyTorch 기반의 구현.
VAE 세미나 이슈 사항에 대한 리뷰.
my github : https://github.com/messy-snail/GAN_PyTorch
[참고]
https://github.com/znxlwm/pytorch-MNIST-CelebA-GAN-DCGAN
https://github.com/taeoh-kim/Pytorch_DCGAN
Radford, Alec, Luke Metz, and Soumith Chintala. "Unsupervised representation learning with deep convolutional generative adversarial networks." arXiv preprint arXiv:1511.06434 (2015).
- The document contains questions for an exam on operating systems and computer architecture. It lists five sections with multiple choice questions in each section covering topics like operating system objectives and functions, real-time operating systems, security issues, and differences between traditional and modern UNIX kernels.
- The exam is worth a total of 100 marks and students must answer five full questions ranging from 4 to 15 marks each. Questions assess understanding of concepts like process states, Linux kernel components, thread implementation, and multiprocessing scheduling approaches.
Story of static code analyzer developmentAndrey Karpov
The document discusses the history and development of static code analyzers. It describes how early tools used regular expressions that were ineffective for complex code analysis. Modern static analyzers overcome these limitations through techniques like type inference, data flow analysis, symbolic execution, and pattern-based analysis. They also leverage method annotations and a mixture of analysis approaches. While machine learning is hyped, static analysis remains very challenging due to the complexity of code and rapid language evolution.
Rainer Grimm, “Functional Programming in C++11”Platonov Sergey
C++ это мультипарадигменный язык, поэтому программист сам может выбирать и совмещать структурный, объектно-ориентированный, обобщенный и функциональный подходы. Функциональный аспект C++ особенно расширился стандартом C++11: лямбда-функции, variadic templates, std::function, std::bind. (язык доклада: английский).
FPGA Implementation of A New Chien Search Block for Reed-Solomon Codes RS (25...IJERA Editor
The Reed-Solomon codes RS are widely used in communication systems, in particular forming part of the specification for the ETSI digital terrestrial television standard. In this paper a simple algorithm for error detection in the Chien Search block is proposed. This algorithm is based on a simple factorization of the error locator polynomial, which allows reducing the number of components required to implement the proposed algorithm on FPGA board. Consequently, it reduces the power consumption with a percentage which can reach 50 % compared to the basic RS decoder. First, we developed the design of Chien Search Block Second, we generated and simulated the hardware description language source code using Quartus software tools,finally we implemented the proposed algorithm of Chien search block for Reed-Solomon codesRS (255, 239) on FPGA board to show both the reduced hardware resources and low complexity compared to the basic algorithm.
Data structures cs301 power point slides lecture 03Nasir Mehmood
The document discusses linked lists and C++ code for implementing a linked list. It includes definitions of a Node class to represent individual nodes, with fields for storing data and pointers to other nodes. It also defines a List class for managing the overall linked list, including functions for adding new nodes to the list. Diagrams show how nodes are linked and stored non-contiguously in memory. The code provided implements adding new nodes to the front or end of the linked list by updating pointer references between nodes.
The document discusses algorithms complexity and data structures efficiency. It covers topics like asymptotic notation to analyze algorithm complexity, different time and memory complexities like constant, logarithmic, linear, quadratic, and exponential. Examples are provided to illustrate complexity calculations for algorithms with operations on arrays, matrices and recursion. Choosing the right data structures depends on the algorithm complexity and problem requirements.
The document discusses linked lists and C++ code for implementing them. It describes how a linked list is structured in memory using nodes that point to the next node. It also shows the Node class definition used to create nodes, and the List class with methods like add() to insert new nodes into the linked list.
An optimal and progressive algorithm for skyline queries slideWooSung Choi
The document presents an optimal and progressive algorithm for processing skyline queries using an R-tree index. It discusses two strategies - recursive nearest neighbor queries and a branch and bound skyline algorithm. The recursive NN query approach requires additional processing to eliminate duplicate results for higher dimensions, while the branch and bound skyline algorithm prunes non-skyline points during traversal to directly generate the skyline without duplicates. The algorithm processes the R-tree in a best-first manner by maintaining a priority queue of tree nodes ordered by their minimum possible skyline size.
This document contains a 20 question multiple choice quiz on computer science topics. The questions cover areas like algorithms, data structures, complexity analysis, logic, automata theory and databases. Sample questions ask about the minimum number of multiplications needed to evaluate a polynomial, the expected value of the smallest number in a random sample, and the recovery procedure after a database system crash during transaction logging.
This week, Luke Pearson (Polychain Capital) and Joshua Fitzgerald (Anoma) present their work on Plonkup, a protocol that combines Plookup and PLONK into a single, efficient protocol. The protocol relies on a new hash function, called Reinforced Concrete, written by Dmitry Khovratovich. The three of them will present their work together at this week's edition of zkStudyClub!
Slides:
---
To Follow the Zero Knowledge Podcast us at https://www.zeroknowledge.fm
To the listeners of Zero Knowledge Podcast, if you like what we do:
- Follow us on Twitter - @zeroknowledgefm
- Join us on Telegram - https://t.me/joinchat/TORo7aknkYNLHmCM
- Support our Gitcoin Grant - https://gitcoin.co/grants/329/zero-knowledge-podcast-2
- Support us on Patreon - https://www.patreon.com/zeroknowledge
The document discusses binary index trees (also called Fenwick trees) and segment trees, which are data structures that allow efficient querying of array prefixes and intervals. Binary index trees support adding values to array elements and retrieving prefix sums in O(log n) time. Segment trees similarly support adding values and finding maximum/minimum values in intervals in O(log n) time. Both achieve faster query times than naive solutions by representing the array as a tree structure.
This document provides an introduction to exploring and visualizing data using the R programming language. It discusses the history and development of R, introduces key R packages like tidyverse and ggplot2 for data analysis and visualization, and provides examples of reading data, examining data structures, and creating basic plots and histograms. It also demonstrates more advanced ggplot2 concepts like faceting, mapping variables to aesthetics, using different geoms, and combining multiple geoms in a single plot.
The document discusses mutating and testing tests. It introduces the concept of mutation analysis, where tests are evaluated by seeding real bugs into the code and checking if the tests detect these bugs. The document provides an example of applying mutation analysis to a factorial function code and test cases. It finds bugs in the test cases like weak oracles and missing test inputs. The document also compares the Pit mutation testing tool with the Descartes tool, finding Descartes generates fewer but coarser-grained mutants, making it more scalable for large projects.
This document contains a sample paper for the CS GATE exam from 2009. It includes 56 multiple choice questions worth 1 or 2 marks each. The questions cover topics such as computer organization, operating systems, algorithms, theory of computation, programming and data structures. An excerpt of the question paper is provided in the document for reference.
PVS-Studio team experience: checking various open source projects, or mistake...Andrey Karpov
To let the world know about our product, we check open-source projects. By the moment we have checked 245 projects. A side effect: we found 9574 errors and notified the authors about them.
ZK Study Club: Sumcheck Arguments and Their ApplicationsAlex Pruden
Talk given at the ZK Study Club by Jonathan Bootle and Katerina Sotiraki about the universality of sumcheck arguments and their importance in zero-knowledge cryptography.
This document contains links and code snippets related to Groovy and GitHub Gists. It includes examples of using Groovy for tasks like playing MIDI notes, generating musical scores, adding nodes to a Jenkins server, and calculating factorials in different styles from a newbie to an expert programmer. The document also references a Greasemonkey script for running a Groovy web console in Firefox.
쉽게 설명하는 GAN (What is this? Gum? It's GAN.)Hansol Kang
The document discusses generative adversarial networks (GANs). It begins with an introduction to GANs, describing their concept and training process. It then reviews a seminal GAN paper, discussing its mathematical formulation of GAN training as a minimax game and theoretical results showing global optimality can be achieved. The document concludes by outlining the configuration, implementation, and flowchart for a GAN experiment.
The document discusses skyline queries and algorithms for computing skylines. It begins by defining skylines and providing examples. It then discusses two main options for implementing skyline queries: extending SQL with a skyline operator, or building skylines on top of relational databases using nested SQL queries. The document focuses on algorithms for computing skylines, including the block-nested loops algorithm, divide and conquer algorithm, and algorithms using B-trees and R-trees. It also discusses combining skyline queries with joins and top-N queries. Experimental results show divide and conquer performs best for multidimensional skylines while block-nested loops is better for small skylines.
The document discusses various topics related to computer graphics and visualization:
i) It explains the concept of pinhole camera and finds the coordinates of a projected point on a film mounted inside the camera box. It also defines the field of view.
ii) It explains the graphics pipeline and its components.
iii) It explains the concept of transformations in homogeneous coordinates and finds the transformation matrix and its inverse for various transformations including rotation.
zkStudy Club: Subquadratic SNARGs in the Random Oracle ModelAlex Pruden
Slides for Eylon Yogev's (Bar-Ilan University) presentation at ZKStudyClub, covering his new work (co-authored w/ Alessandro Chiesa of UC Berkeley) about SNARGs in the random oracle model of sub- quadratic complexity.
Link to the original paper: https://eprint.iacr.org/2021/281.pdf
This document contains information about a Data Structures and Algorithms course taught by Associate Professor Yusuf Sahillioğlu at Middle East Technical University. It provides details about the course instructor, textbook, grading breakdown, course outline covering topics like sorting, lists, trees and graphs, and motivational examples demonstrating how data structures can be used to efficiently store and process data. It also includes an introduction to programming in C++ covering object-oriented concepts like classes, objects, encapsulation and information hiding.
This document contains information about a Data Structures and Algorithms course taught by Professor Yusuf Sahillioğlu at Middle East Technical University. It provides details about the course objectives, textbook, grading breakdown, course outline covering topics like sorting, lists, trees and graphs, and motivational examples demonstrating how data structures can be used to efficiently store and process data. It also introduces some basic C++ concepts like classes, objects, encapsulation and information hiding that will be used in the course.
Rainer Grimm, “Functional Programming in C++11”Platonov Sergey
C++ это мультипарадигменный язык, поэтому программист сам может выбирать и совмещать структурный, объектно-ориентированный, обобщенный и функциональный подходы. Функциональный аспект C++ особенно расширился стандартом C++11: лямбда-функции, variadic templates, std::function, std::bind. (язык доклада: английский).
FPGA Implementation of A New Chien Search Block for Reed-Solomon Codes RS (25...IJERA Editor
The Reed-Solomon codes RS are widely used in communication systems, in particular forming part of the specification for the ETSI digital terrestrial television standard. In this paper a simple algorithm for error detection in the Chien Search block is proposed. This algorithm is based on a simple factorization of the error locator polynomial, which allows reducing the number of components required to implement the proposed algorithm on FPGA board. Consequently, it reduces the power consumption with a percentage which can reach 50 % compared to the basic RS decoder. First, we developed the design of Chien Search Block Second, we generated and simulated the hardware description language source code using Quartus software tools,finally we implemented the proposed algorithm of Chien search block for Reed-Solomon codesRS (255, 239) on FPGA board to show both the reduced hardware resources and low complexity compared to the basic algorithm.
Data structures cs301 power point slides lecture 03Nasir Mehmood
The document discusses linked lists and C++ code for implementing a linked list. It includes definitions of a Node class to represent individual nodes, with fields for storing data and pointers to other nodes. It also defines a List class for managing the overall linked list, including functions for adding new nodes to the list. Diagrams show how nodes are linked and stored non-contiguously in memory. The code provided implements adding new nodes to the front or end of the linked list by updating pointer references between nodes.
The document discusses algorithms complexity and data structures efficiency. It covers topics like asymptotic notation to analyze algorithm complexity, different time and memory complexities like constant, logarithmic, linear, quadratic, and exponential. Examples are provided to illustrate complexity calculations for algorithms with operations on arrays, matrices and recursion. Choosing the right data structures depends on the algorithm complexity and problem requirements.
The document discusses linked lists and C++ code for implementing them. It describes how a linked list is structured in memory using nodes that point to the next node. It also shows the Node class definition used to create nodes, and the List class with methods like add() to insert new nodes into the linked list.
An optimal and progressive algorithm for skyline queries slideWooSung Choi
The document presents an optimal and progressive algorithm for processing skyline queries using an R-tree index. It discusses two strategies - recursive nearest neighbor queries and a branch and bound skyline algorithm. The recursive NN query approach requires additional processing to eliminate duplicate results for higher dimensions, while the branch and bound skyline algorithm prunes non-skyline points during traversal to directly generate the skyline without duplicates. The algorithm processes the R-tree in a best-first manner by maintaining a priority queue of tree nodes ordered by their minimum possible skyline size.
This document contains a 20 question multiple choice quiz on computer science topics. The questions cover areas like algorithms, data structures, complexity analysis, logic, automata theory and databases. Sample questions ask about the minimum number of multiplications needed to evaluate a polynomial, the expected value of the smallest number in a random sample, and the recovery procedure after a database system crash during transaction logging.
This week, Luke Pearson (Polychain Capital) and Joshua Fitzgerald (Anoma) present their work on Plonkup, a protocol that combines Plookup and PLONK into a single, efficient protocol. The protocol relies on a new hash function, called Reinforced Concrete, written by Dmitry Khovratovich. The three of them will present their work together at this week's edition of zkStudyClub!
Slides:
---
To Follow the Zero Knowledge Podcast us at https://www.zeroknowledge.fm
To the listeners of Zero Knowledge Podcast, if you like what we do:
- Follow us on Twitter - @zeroknowledgefm
- Join us on Telegram - https://t.me/joinchat/TORo7aknkYNLHmCM
- Support our Gitcoin Grant - https://gitcoin.co/grants/329/zero-knowledge-podcast-2
- Support us on Patreon - https://www.patreon.com/zeroknowledge
The document discusses binary index trees (also called Fenwick trees) and segment trees, which are data structures that allow efficient querying of array prefixes and intervals. Binary index trees support adding values to array elements and retrieving prefix sums in O(log n) time. Segment trees similarly support adding values and finding maximum/minimum values in intervals in O(log n) time. Both achieve faster query times than naive solutions by representing the array as a tree structure.
This document provides an introduction to exploring and visualizing data using the R programming language. It discusses the history and development of R, introduces key R packages like tidyverse and ggplot2 for data analysis and visualization, and provides examples of reading data, examining data structures, and creating basic plots and histograms. It also demonstrates more advanced ggplot2 concepts like faceting, mapping variables to aesthetics, using different geoms, and combining multiple geoms in a single plot.
The document discusses mutating and testing tests. It introduces the concept of mutation analysis, where tests are evaluated by seeding real bugs into the code and checking if the tests detect these bugs. The document provides an example of applying mutation analysis to a factorial function code and test cases. It finds bugs in the test cases like weak oracles and missing test inputs. The document also compares the Pit mutation testing tool with the Descartes tool, finding Descartes generates fewer but coarser-grained mutants, making it more scalable for large projects.
This document contains a sample paper for the CS GATE exam from 2009. It includes 56 multiple choice questions worth 1 or 2 marks each. The questions cover topics such as computer organization, operating systems, algorithms, theory of computation, programming and data structures. An excerpt of the question paper is provided in the document for reference.
PVS-Studio team experience: checking various open source projects, or mistake...Andrey Karpov
To let the world know about our product, we check open-source projects. By the moment we have checked 245 projects. A side effect: we found 9574 errors and notified the authors about them.
ZK Study Club: Sumcheck Arguments and Their ApplicationsAlex Pruden
Talk given at the ZK Study Club by Jonathan Bootle and Katerina Sotiraki about the universality of sumcheck arguments and their importance in zero-knowledge cryptography.
This document contains links and code snippets related to Groovy and GitHub Gists. It includes examples of using Groovy for tasks like playing MIDI notes, generating musical scores, adding nodes to a Jenkins server, and calculating factorials in different styles from a newbie to an expert programmer. The document also references a Greasemonkey script for running a Groovy web console in Firefox.
쉽게 설명하는 GAN (What is this? Gum? It's GAN.)Hansol Kang
The document discusses generative adversarial networks (GANs). It begins with an introduction to GANs, describing their concept and training process. It then reviews a seminal GAN paper, discussing its mathematical formulation of GAN training as a minimax game and theoretical results showing global optimality can be achieved. The document concludes by outlining the configuration, implementation, and flowchart for a GAN experiment.
The document discusses skyline queries and algorithms for computing skylines. It begins by defining skylines and providing examples. It then discusses two main options for implementing skyline queries: extending SQL with a skyline operator, or building skylines on top of relational databases using nested SQL queries. The document focuses on algorithms for computing skylines, including the block-nested loops algorithm, divide and conquer algorithm, and algorithms using B-trees and R-trees. It also discusses combining skyline queries with joins and top-N queries. Experimental results show divide and conquer performs best for multidimensional skylines while block-nested loops is better for small skylines.
The document discusses various topics related to computer graphics and visualization:
i) It explains the concept of pinhole camera and finds the coordinates of a projected point on a film mounted inside the camera box. It also defines the field of view.
ii) It explains the graphics pipeline and its components.
iii) It explains the concept of transformations in homogeneous coordinates and finds the transformation matrix and its inverse for various transformations including rotation.
zkStudy Club: Subquadratic SNARGs in the Random Oracle ModelAlex Pruden
Slides for Eylon Yogev's (Bar-Ilan University) presentation at ZKStudyClub, covering his new work (co-authored w/ Alessandro Chiesa of UC Berkeley) about SNARGs in the random oracle model of sub- quadratic complexity.
Link to the original paper: https://eprint.iacr.org/2021/281.pdf
This document contains information about a Data Structures and Algorithms course taught by Associate Professor Yusuf Sahillioğlu at Middle East Technical University. It provides details about the course instructor, textbook, grading breakdown, course outline covering topics like sorting, lists, trees and graphs, and motivational examples demonstrating how data structures can be used to efficiently store and process data. It also includes an introduction to programming in C++ covering object-oriented concepts like classes, objects, encapsulation and information hiding.
This document contains information about a Data Structures and Algorithms course taught by Professor Yusuf Sahillioğlu at Middle East Technical University. It provides details about the course objectives, textbook, grading breakdown, course outline covering topics like sorting, lists, trees and graphs, and motivational examples demonstrating how data structures can be used to efficiently store and process data. It also introduces some basic C++ concepts like classes, objects, encapsulation and information hiding that will be used in the course.
This document discusses lists as an abstract data structure and their common operations. Lists can be implemented using arrays or linked lists, each with different runtimes for operations like accessing, inserting, or erasing elements. Doubly linked lists provide faster access than singly linked lists. The Standard Template Library vector class can also be used to implement lists. Strings are a special case of lists where elements are restricted to characters. Memory usage and runtimes must be balanced when choosing a data structure.
This document discusses queues as a data structure. It defines queues as lists that only allow insertions at one end and deletions at the other end, following a First-In First-Out (FIFO) ordering. Common queue operations like add, remove, and peek are introduced. Examples of queues in computer science and real world are provided, like print job queues and lines. Implementations of queues using arrays and linked lists are briefly described.
The document discusses ESL (electronic system level) design and some challenges with adopting ESL flows that use C/C++ as a design entry language. It provides examples of how C/C++ code can unintentionally result in inefficient hardware implementations if the designer does not consider the hardware implications. The document advocates that ESL adoption needs to be driven by designer needs and preferences rather than management decisions. It also argues that ESL tools need to provide predictability of results, education for designers on the hardware implications of different coding styles, and robust verification methods for ESL to be widely adopted.
This document contains solutions to exercises from chapters 1-8 of an algorithms textbook. The solutions include code snippets, explanations, and test cases. Key points addressed include asymptotic analysis of algorithms, data structures like linked lists and stacks/queues, and recursion.
The document contains two questions asking to implement data structures in C++. Question 1 asks to implement methods for a singly linked list including returning size, printing, checking containment, adding, and removing values. Question 2 asks to implement methods for a queue using an array including initializing, checking for empty/full, accessing front/back, adding, and removing elements. Sample code is provided for both a linked list and queue implementation with the required methods.
«Отладка в Python 3.6: Быстрее, Выше, Сильнее» Елизавета Шашкова, JetBrainsit-people
The document discusses debugging in Python 3.6. It describes tracing and frame evaluation debuggers. Tracing debuggers slow code execution significantly by calling the tracing function on every line. Python 3.6 introduced a new frame evaluation API that allows evaluating frames directly, avoiding the performance issues of tracing. The document demonstrates how to build a debugger using this approach, including setting breakpoints and stepping through code by inserting temporary breakpoints on each line. Frame evaluation allows building a debugger that is faster than tracing debuggers without significant performance penalties.
This document contains a lab manual for data structures programming. It outlines various exercises including representing sparse matrices using arrays and linked lists, implementing stack and queue data structures using arrays and linked lists, and performing operations on singly, doubly and circular linked lists. It also covers binary tree traversals, binary search tree implementation and operations, and algorithms including heap sort, quick sort, depth first search, breadth first search and Dijkstra's algorithm.
Consider this code using the ArrayBag of Section 5.2 and the Locat.docxmaxinesmith73660
Consider this code using the ArrayBag of Section 5.2 and the Location class from Chapter 2. What is the output?
Location i = new Location(0, 3);
Location j = new Location(0, 3);
b.add(i);
b.add(j);
System.out.println(b.countOccurrences(i));
A. 0
B. 1
C. 2
D. 3
Suppose that b and c are Integer objects. A typical use of the clone method looks like this:
b = (Integer) c.clone( );
Write a short clear explanation of why the (Integer) type cast is required in this typical example.
A. obj = s;
B. s = obj;
C. s = (String) obj;
D. Two or more answers are correct.
Suppose that obj is an Object variable and s is a String variable. Which of the following statements
is a correctly-compiling widening conversion? Don't worry about possible run-time exceptions
A. obj = s;
B. s = obj;
C. s = (String) obj;
D. Two or more answers are correct.
Suppose that x and y are reference variables and a program activates x.equals(y). What occurs if x is the null reference?
A. A NullPointerException occurs
B. It always returns true.
C. It always returns false.
D. It returns true if y is also a null reference; otherwise it returns false.
Consider the implementation of the Stack using a partially-filled array.
What goes wrong if we try to store the top of the Stack at location [0] and the bottom of the Stack at the last used position of the array?
A. Both peek and pop would require linear time.
B. Both push and pop would require linear time.
C. The Stack could not be used to check balanced parentheses.
D. The Stack could not be used to evaluate postfix expressions.
Write some lines of code that declares an Integer object, using the Integer wrapper class.
Assign the value 42 to this object, then copy this value from the Integer object to an ordinary int variable.
Consider the usual algorithm for determining whether a sequence of parentheses is balanced.
What is the maximum number of parentheses that will appear on the stack AT ANY ONE TIME when the algorithm analyzes: (()(())(()))?
A. 1
B. 2
C. 3
D. 4
E. 5 or more
Consider the usual algorithm to convert an infix expression to a postfix expression.
Suppose that you have read 10 input characters during a conversion and that the
stack now contains the symbols as shown below. Suppose that you read and process
the 11th symbol of the input. What symbol is at the top of the stack in the case where
the 11th symbol is each of the choices shown?
Which of the following stack operations could result in stack underflow?
Answer
A. is_empty
B. pop
C. push
D. Two or more of the above answers
What is the value of the postfix expression 6 3 2 4 + - *:
Answer
A. Something between -15 and -100
B. Something between -5 and -15
C. Something between 5 and -5
D. Something between 5 and 15
E. Something between 15 and 100
1. An array o.
The document discusses how Python code is executed. It explains that Python code is first compiled into code objects then executed via a frame object on the stack. Code objects contain details like function names and constants while frame objects contain details like the current code, local and global variables. It also describes the main components involved in execution like opcodes, bytecodes, and the CPython interpreter which evaluates bytecodes by calling corresponding operations.
The document discusses queues and priority queues. It defines a queue as a waiting line that grows by adding elements to its end and shrinks by taking elements from its front. Common queue operations include enqueue, dequeue, front, clear, isEmpty. Queues follow FIFO order. Priority queues allow elements to be dequeued out of order based on priority. Array and linked list implementations of regular and priority queues are presented. Applications discussed include round robin scheduling, waiting lists, and shared resource access.
The document discusses stacks and queues as fundamental data structures. It covers stack and queue operations like push, pop, enqueue, and dequeue. It presents implementations of stacks and queues using both arrays and linked lists. It discusses dynamic resizing of arrays to allow for efficient pushing and popping. The document also covers using generics to create parameterized data structures like Stack<Item> that avoid casting. Several applications of stacks are described, including evaluating arithmetic expressions using a two-stack algorithm and modeling function calls in a compiler using a run-time stack.
Lock-free algorithms use atomic operations instead of locks to allow for thread-safe concurrent access to shared data structures. This avoids issues like deadlocks but makes implementation more complex. Common atomic operations include compare-and-swap (CAS) and load-linked/store-conditional (LL/SC). A key challenge is avoiding the ABA problem where a value is changed back to its original. Solutions involve adding version numbers or using more advanced operations like CAS2. Overall, lock-free approaches can improve performance over locking but require careful design to ensure correctness and avoid data corruption between threads.
Classes allow programmers to create new types that model real-world objects. A class defines both data attributes and built-in operations that can operate on that data. C++ provides built-in classes like string and iostream that add powerful functionality to the language. The string class allows easy storage and manipulation of strings, while the iostream classes (istream and ostream) define objects like cin and cout for input/output. These classes provide many useful built-in operations that make input/output powerful yet easy to use.
This document contains multiple choice and short answer questions about data structures such as arrays, linked lists, stacks, queues, and trees. The multiple choice questions test knowledge of the basic properties and applications of these data structures. The short answer questions involve coding examples using recursion, stacks, queues, and linked lists to solve problems.
This document discusses various techniques for optimizing Python code, including:
1. Using the right algorithms and data structures to minimize time complexity, such as choosing lists, sets or dictionaries based on needed functionality.
2. Leveraging Python-specific optimizations like string concatenation, lookups, loops and imports.
3. Profiling code with tools like timeit, cProfile and visualizers to identify bottlenecks before optimizing.
4. Optimizing only after validating a performance need and starting with general strategies before rewriting hotspots in Python or other languages. Premature optimization can complicate code.
A stack is a last-in, first-out (LIFO) data structure where elements can only be added or removed from one end of the structure, called the top. The std::stack class in C++ uses an underlying container like vector or deque to store elements. It provides functions like push() to add elements, pop() to remove elements, and top() to access the top element. Example code shows how to use a stack to store integers, display the size, insert and remove elements, and check the top element.
The document discusses data structures and abstract data types (ADTs). It describes lists, stacks, and queues. Lists can be implemented using arrays or linked lists. Linked lists allow for faster insertion and deletion compared to arrays. Stacks follow a last-in, first-out order, while queues follow a first-in, first-out order. Common operations on stacks and queues include push, pop, enqueue, and dequeue. The document provides examples of how stacks and queues can be used in applications such as bracket matching, calculators, and job queues.
This document describes a scalable, versioned document store built within PostgreSQL. It discusses the motivation for moving from multiple data stores and repositories to a single PostgreSQL database. It then covers the design of storing immutable content as Merkle DAG nodes linked by cryptographic hashes, with references and tags allowing different versions. It also explains how the system was implemented using PostgreSQL functions to generate hashes, insert nodes, and handle migrations from the original data model.
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1. C++ Concurrency in Action Study
C++ Korea
C++ Korea
C++ Concurrency in Action
Study C++ Korea 박 동하 (luncliff@gmail.com)
C++ Korea 최두선 ( returns@lycos.co.kr )
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Performance Test ( 시나리오 )
62
void test( int aThreadID,
lock_free_queue<std::string> * aLockFreeQueue,
int aCount )
{
for ( int i = 0; i < aCount; i++ )
{
aLockFreeQueue->push( "TEST1234567890" );
}
for ( int i = 0; i < aCount; i++ )
{
aLockFreeQueue->pop();
}
}
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Performance Test ( 시나리오 )
63
TIME(1) BSD General Commands Manual TIME(1)
NAME
time -- time command execution
SYNOPSIS
time [-lp] utility
DESCRIPTION
The time utility executes and times utility. After the utility finishes, time writes the
total time elapsed, the time consumed by system overhead, and the time used to execute
utility to the standard error stream. Times are reported in seconds.
DoO@DooSeonui-MacBook-Air ~/Work/Study/Whatever/LockFreeQueue/build master ● time
shell 0.09s user 0.09s system 5% cpu 3.440 total
children 0.11s user 0.20s system 8% cpu 3.440 total
User User Mode 에서 CPU 를 사용한 시간
sysem Kernel Mode 에서 CPU 를 사용한 시간
total 총 CPU 를 사용한 시간
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Performance Test ( Test 환경)
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$ g++ -v
Configured with: --prefix=/Applications/Xcode.app/Contents/Developer/usr --with-gxx-include-dir=/usr/include/c++/4.2.1
Apple LLVM version 7.0.2 (clang-700.1.81)
Target: x86_64-apple-darwin15.3.0
Thread model: posix
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Performance Test ( 수행시간 )
65
1 4 8 16 32 64
ThreadSafeQueue user 0.72 11.88 23.25 47.08 97.53 211.40
sys 0.04 34.70 72.09 150.95 322.91 723.82
real 0.771 41.083 84.63 174.07 361.09 780
LockFreeQueue user 0.82 11.91 29.05 74.84 201.91 537.76
sys 0.04 0.2 0.4 0.85 5.69 32.26
real 0.86 3.23 7.43 19.249 53.122 155.63
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Performance Test ( 수행시간 )
66
0
250
500
750
1000
1 4 8 16 32 64 1 4 8 16 32 64
값축
제목
sys user
ThreadSafeQueue LockFreeQueue
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Performance Test ( CPU 사용량 )
67
1 4 8 16 32 64
ThreadSafeQueue 99% 113% 112% 113% 116% 119%
LockFreeQueue 99% 374% 394% 393% 390% 365%
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Performance Test ( CPU 사용량 )
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0%
100%
200%
300%
400%
500%
1 4 8 16 32 64
값축
제목
ThreadSafeQueue LockFreeQueue
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Performance Test ( Test 환경)
69
$ g++ -v
Using built-in specs.
COLLECT_GCC=g++
COLLECT_LTO_WRAPPER=/usr/lib/gcc/x86_64-linux-gnu/4.8/lto-wrapper
Target: x86_64-linux-gnu
Configured with: ../src/configure -v --with-pkgversion='Ubuntu 4.8.4-2ubuntu1~14.04' --with-bugurl=file:///usr/share/doc/gcc-4.8/README.Bugs --enable-
languages=c,c++,java,go,d,fortran,objc,obj-c++ --prefix=/usr --program-suffix=-4.8 --enable-shared --enable-linker-build-id --libexecdir=/usr/lib --without-included-gettext --enable-threads=posix -
-with-gxx-include-dir=/usr/include/c++/4.8 --libdir=/usr/lib --enable-nls --with-sysroot=/ --enable-clocale=gnu --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-gnu-unique-object --
disable-libmudflap --enable-plugin --with-system-zlib --disable-browser-plugin --enable-java-awt=gtk --enable-gtk-cairo --with-java-home=/usr/lib/jvm/java-1.5.0-gcj-4.8-amd64/jre --enable-java-
home --with-jvm-root-dir=/usr/lib/jvm/java-1.5.0-gcj-4.8-amd64 --with-jvm-jar-dir=/usr/lib/jvm-exports/java-1.5.0-gcj-4.8-amd64 --with-arch-directory=amd64 --with-ecj-jar=/usr/share/java/eclipse-
ecj.jar --enable-objc-gc --enable-multiarch --disable-werror --with-arch-32=i686 --with-abi=m64 --with-multilib-list=m32,m64,mx32 --with-tune=generic --enable-checking=release --build=x86_64-
linux-gnu --host=x86_64-linux-gnu --target=x86_64-linux-gnu
Thread model: posix
gcc version 4.8.4 (Ubuntu 4.8.4-2ubuntu1~14.04)
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70
1 4 8 16 32 64
ThreadSafeQueue user 0.98 7.53 12.85 26.29 52.47 112.23
sys 0.03 6.52 14.01 24.53 50.38 111.34
real 1.013 4.727 8.99 18.80 39.62 77.57
LockFreeQueue user 0.52 7.08 15.52 39.81 82.67 380.45
sys 0.06 0.27 1.17 2.6 5.32 11.61
real 0.538 2.291 5.87 16.07 35.83 129.21
LockFreeQueue2 user 0.58 9.73 18.97 26.69 50.52 103.25
sys 0.06 0.34 1.51 2.90 5.88 13.70
real 0.644 3.031 6.681 12.813 26.40 44.34
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Performance Test ( 수행시간 )
71
0
100
200
300
400
500
1 4 8 16 32 64 1 4 8 16 32 64 1 4 8 16 32 64
값축
제목
user sys
ThreadSafeQueue LockFreeQueue LockFreeQueue2
72. C++ Concurrency in Action Study
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Performance Test ( CPU 사용량 )
72
1 4 8 16 32 64
ThreadSafeQueue 99% 297% 298% 270% 259% 288%
LockFreeQueue 99% 320% 284% 263% 248% 303%
LockFreeQueue2 99% 332% 306% 254% 213% 263%
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Performance Test ( CPU 사용량 )
73
0%
100%
200%
300%
400%
1 4 8 16 32 64
값축
제목
ThreadSafeQueue LockFreeQueue LockFreeQueue2
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Guidelines for writing
lock free data structure
75. C++ Concurrency in Action Study
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use std::memory_order_seq_cst for prototyping
75
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use a lock-free memory reclamation scheme
76
78. C++ Concurrency in Action Study
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watch out for ABA Problem
78
From The Art of Multiprocessor Programming
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watch out for ABA Problem
79
From The Art of Multiprocessor Programming
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watch out for ABA Problem
80
Thread1 Thread2 Thread3 Thread4
1 POP()
2
POP()
3
PUSH()
4
PUSH()
5
POP()
7
head.CAS( A, B )
Queue
A Head
B Tail
Free
Memory List
C
D
E
81. C++ Concurrency in Action Study
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watch out for ABA Problem
81
Thread1 Thread2 Thread3 Thread4
1 POP()
2
POP()
-> free A
3
PUSH()
4
PUSH()
5
POP()
7
head.CAS( A, B )
Queue
B
Head
Tail
Free
Memory List
A
C
D
E
82. C++ Concurrency in Action Study
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watch out for ABA Problem
82
Thread1 Thread2 Thread3 Thread4
1 POP()
2
POP()
-> free A
3
PUSH()
-> new A
4
PUSH()
5
POP()
7
head.CAS( A, B )
Queue
B Head
A Tail
Free
Memory List
C
D
E
83. C++ Concurrency in Action Study
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watch out for ABA Problem
83
Thread1 Thread2 Thread3 Thread4
1 POP()
2
POP()
-> free A
3
PUSH()
-> new A
4
PUSH()
-> new C
5
POP()
7
head.CAS( A, B )
Queue
B Head
A
C Tail
Free
Memory List
D
E
84. C++ Concurrency in Action Study
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watch out for ABA Problem
84
Thread1 Thread2 Thread3 Thread4
1 POP()
2
POP()
-> free A
3
PUSH()
-> new A
4
PUSH()
-> new C
5
POP()
-> free B
7
head.CAS( A, B )
Queue
A
C Tail
Free
Memory List
B Head
D
E
95. C++ Concurrency in Action Study
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reference
https://forums.manning.com/
http://en.cppreference.com/
intel.com
http://libcds.sourceforge.net
https://www.threadingbuildingblocks.org
https://www.threadingbuildingblocks.org/intel-tbb-tutorial
http://www.boost.org/doc/libs/1_60_0/doc/html/lockfree.html
95