parallel computing

Intel Software Conference - Parallel Computing

O Intel Software Conference - Parallel Computing é um evento gratuito destinado a:

  • Líderes do mercado de tecnologia
  • Desenvolvedores de software paralelo.

O evento acontece nos dias 6 e 7 de Agosto (São Paulo) e 12 e 13 de Agosto (Rio de Janeiro) e contará com a presença de palestrantes internacionais (Intel EUA e Intel Alemanha).

  • 开发人员
  • 服务器
  • C/C++
  • Fortran
  • Intel® Cluster Studio XE
  • 英特尔® VTune™ 放大器 XE
  • parallel computing
  • HPC
  • computação paralela
  • paralelismo
  • Cluster
  • Desempenho
  • performance
  • software
  • От последовательного кода к параллельному за пять шагов c Intel® Advisor XE

    Если вы давно разрабатываете многопоточные приложения, наверняка вы сталкивались с распараллеливанием уже существующего последовательного кода. Или наоборот, вы новичок в параллельном программировании, а перед вами встали задачи оптимизации проекта и улучшения масштабируемости, которые тоже могут быть решены путём распараллеливания отдельных участков программы. 

    Новый инструмент Intel® Advisor XE поможет вам распараллелить приложение, потратив на это минимум сил и времени.

    Introduction to Parallel Programming with Java

    Develop programs that take advantage of multi-core platforms by applying fundamental concepts of parallel programming.

    After completing this course, you will be able to:

    • Recognize opportunities for parallel computing
    • Use basic implementations for domain and task parallelism
    • Ensure correctness by identifying and resolving race conditions and deadlocks
    • Improve performance by selective code modifications and load balancing

    Introduction to Parallel Programming video lecture series – Part 09 “Implementing a Task Decomposition”

    The lecture given here is the ninth part in the “Introduction to Parallel Programming” video series. This part describes how design and implement a task decomposition solution. An illustrative example for solving the 8 Queens problem is used. Multiple approaches are presented with the pros and cons for each described. After the approach is decided upon, code modifications using OpenMP are presented. Potential data race errors with a shared stack data structure holding board configurations (the tasks to be processed) are offered and a solution is found and implemented.

    Introduction to Parallel Programming video lecture series – Part 08 “OpenMP for Task Decomposition”

    The lecture given here is the eighth part in the “Introduction to Parallel Programming” video series. This part describes how the OpenMP task pragma works and how it is different from the previous worksharing pragmas. A small linked list processing code example is used to illustrate how independent operation within a while-loop can be parallelized. Since recursive functions, where the recursive calls are independent, can be executed in parallel, the OpenMP task construct is used to parallelize the computation of a desired member from the Fibonacci sequence.

    Introduction to Parallel Programming hands-on programming lab – Prime Counter

    This hands-on exercise lab, Prime Counter, is a programming lab associated with the video lecture “Reducing Parallel Overhead” (Part 12) from the “Introduction to Parallel Programming” series. This problem seeks to parallelize an application to count prime numbers within a given range, but do so in a less brute force way than the previous prime number finding applicaiton. The lab contents include source files and written instructions to guide the programmer in converting the serial source code into an equivalent parallel version using OpenMP.

    Introduction to Parallel Programming hands-on programming lab – Iterative Quicksort

    This hands-on exercise lab, Iterative Quicksort, is a programming lab associated with the video lecture “Reducing Parallel Overhead” (Part 12) from the “Introduction to Parallel Programming” series. This problem seeks to parallelize an iterative implementation of the Quicksort algorithm. The lab contents include source files and written instructions to guide the programmer in converting the serial source code into an equivalent parallel version using OpenMP.

    订阅 parallel computing