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- Parallel Programming &
- CS 470 Spring 2018
- Effective Data Parallel Computing on Multicore Processors
- Gossamer: a Lightweight Programming Framework for Multicore Machines∗
- Predictable Parallel Programming with Openmp
- A Course-Based Usability Analysis of Cilk Plus and Openmp Michael Coblenz1, Robert Seacord2, Brad Myers1, Joshua Sunshine1, and Jonathan Aldrich1
- Dense Linear Algebra Factorization in Openmp and Cilk Plus on Intel's
- Mapreduce and Spark (And MPI) (Lecture 22, Cs262a)
- The Cilk System for Parallel Multithreaded Computing
- Intel® Compilers Version 15.0
- SIMD Abstraction and Interfacing with CUDA
- A Scalable and Composable Map-Reduce System
- How to Survive the Multicore Software Revolution (Or at Least Survive the Hype)
- High-Performance and Scalable MPI+X Library for Emerging HPC Clusters & Cloud Platforms
- Intel® Cilk™ Plus Language Extension Specification
- Shared-Memory Parallel Programming with Cilk Plus
- Intel® Threading Building Blocks
- CSE 613: Parallel Programming Lecture 3 ( the Cilk++ Concurrency
- The Implementation of the Cilk-5 Multithreaded Language
- Multicore Programming Models and Their Implementation Challenges
- Cilk: an Efficient Multithreaded Runtime System
- Introduction to Parallel Programming with MPI and Openmp
- Multithreaded Programming in Cilk
- Parallel Programming in Intel Cilk Plus with Autotuning
- CSE 590: Special Topics Course ( Supercomputing ) Lecture 3 ( The
- Parallel Programming. Multicore Processors TODAY, Many-Core Co-Processors READY
- Intel® Threading Building Blocks Tutorial
- Improving Averaging Filter Performance Using Intel® Cilk™ Plus
- Parallel Languages and Platforms
- Parallel Programming Models
- Bigdl: a Distributed Deep Learning Library on Spark Zhichao Li Big Data Technology Team, Software and Service Group, Intel
- HPCS Languages: Fortress, Chapel, and X10
- Intel® Cilk++ SDK Programmer's Guide
- An Overview of Explicit Parallel Programming Languages Dounia Khaldi, Pierre Jouvelot, Corinne Ancourt, François Irigoin
- What's New August 2015
- QR Factorization in Openmp and Cilk Plus: Development Experience and Performance Analysis
- Introduction to Cilk Programming
- Cilk and Openmp (Lecture 20, Cs262a)
- Characterizing and Improving the Performance of Intel Threading Building Blocks
- Getting Started with Intel® Cilk™ Plus Array Notations
- Intel® DAAL) and Daal4py ▪ Hands-On
- How to Use Intel® DAAL with Spark*
- Introduction to Multicore Programming
- Homework 0 1 Overview 2 Cilk Plus
- Comparison of Threading Programming Models
- Cilk: an Efficient Multithreaded Runtime System
- SIMD: Cilkplus and Openmp
- Tasking and Cilk Plus
- Intel® Software Template Overview
- Work-First and Help-First Scheduling Policies for Async-Finish Task Parallelism
- Modeling Intel® Cilk™ Plus Programs with Unified Modeling Languages
- An Evaluation of Current SIMD Programming Models for C++
- GPU Computing with Openacc Directives
- Redalyc.Parallel Programming Languages on Heterogeneous
- Introduction to Intel Cilk
- Comparison of Threading Programming Models
- A Course-Based Usability Analysis of Cilk Plus and Openmp
- Getting Productivity and Performance with Selective Embedded Just-In-Time Specialization
- Programming Heterogeneous Parallel Architectures Directive
- Designing Efficient HPC, Big Data, Deep Learning, and Cloud Computing Middleware for Exascale Systems