visual computing

Bitonic Sorting

Demonstrates how to implement an efficient sorting routine with the OpenCL™ technology that operates on arbitrary input array of integer values. The sample uses properties of bitonic sequence and principles of sorting networks and enables efficient SIMD-style parallelism through OpenCL vector data types. The code is designed to work well on modern CPUs.
  • Desenvolvedores
  • Linux*
  • Microsoft Windows* (XP, Vista, 7)
  • Microsoft Windows* 8
  • Windows*
  • C/C++
  • Intermediário
  • OpenCL™ Code Builder
  • visual computing
  • OpenCL*
  • Ferramentas de desenvolvimento
  • Arquitetura Intel® Many Integrated Core
  • Computação paralela
  • General Matrix Multiply Sample

    General Matrix Multiply (GEMM) sample demonstrates how to efficiently utilize an OpenCL™ device to perform general matrix multiply operation on two dense square matrices. The primary target devices that are suitable for this sample are the devices with cache memory: Intel® Xeon Phi™ and Intel® Architecture CPU devices.
  • Desenvolvedores
  • Linux*
  • Microsoft Windows* (XP, Vista, 7)
  • Microsoft Windows* 8
  • Windows*
  • C/C++
  • Intermediário
  • OpenCL™ Code Builder
  • visual computing
  • OpenCL*
  • Ferramentas de desenvolvimento
  • Arquitetura Intel® Many Integrated Core
  • Computação paralela
  • Median Filter

    The sample demonstrates how to implement efficient median filter with OpenCL™ standard. This implementation relies on auto-vectorization performed by Intel® SDK for OpenCL Applications compiler.
  • Desenvolvedores
  • Linux*
  • Microsoft Windows* (XP, Vista, 7)
  • Microsoft Windows* 8
  • C/C++
  • Principiante
  • Kit de desenvolvimento Intel® para aplicativos OpenCL™
  • OpenCL*
  • visual computing
  • Ferramentas de desenvolvimento
  • Arquitetura Intel® Many Integrated Core
  • Computação paralela
  • Vetorização
  • Assine o visual computing