Note: OpenCL drivers have been included in all publicly available NVIDIA drivers since October 2009.
The CUDA Toolkit now includes the Visual Profiler for OpenCL as well as the OpenCL Programming Guide, Best Practices Guide, and other developer documentation.

Click here to view all CUDA Toolkit releases OpenCL Conformance Certified

This release includes OpenCL drivers, OpenCL Visual Profiler, OpenCL code samples, and OpenCL Best Practices Guide for the September 2009 public release. For more recent releases, please visit the link above.

Release Highlights

  • OpenCL v1.0 Conformant GPU drivers for all CUDA-enabled GPUs
    • Certified conformance by the Khronos OpenCL Working Group on 12 June 2009
    • Includes support for OpenCL Images and atomics, which enable significant acceleration across many image processing disciplines. For example Medical Imaging, Video Transcoding applications, Machine Vision, Facial Detection and Recognition and more via the following extensions:
      • cl_khr_byte_addressable_store
      • cl_khr_global_int32_base_atomics
      • cl_khr_global_int32_extended_atomics
      • cl_khr_local_int32_base_atomics
      • cl_khr_local_int32_extended_atomics
  • OpenCL Visual Profiler leverages performance instrumentation in NVIDIA's OpenCL drivers and hardware performance signals designed into NVIDIA GPUs. This powerful analysis tool provides developers with insight into performance bottlenecks and opportunities via these key features:
    • Profiling of actual hardware signals, kernel efficiency, and instruction issue rate
    • Timing of memory copies between system memory and GPU dedicated memory
    • Customizable graphs to help developers focus in on problem areas
    • Basic auto-analysis to reveal warp serialization problems
    • Easy import/export to CSV for custom analysis
  • Support for multi-GPU performance scaling has been added to most of the OpenCL code samples, and several new code samples have been added as well, including:
    • oclMedianFilter
    • oclFDTD3d
    • oclRadixSort
    • oclMersenneTwister
    • oclSemirandomGenerator
  • OpenCL Best Practices Guide, designed to help developers using OpenCL on the CUDA architecture implement high performance parallel algorithms and understand best practices for GPU Computing. Chapters on the following topics and more are included in the guide:
    • Heterogeneous Computing with OpenCL
    • Performance Metrics
    • Memory Optimizations
    • NDRange Optimizations
    • Instruction Optimizations
    • Control Flow
    • Performance Optimization Strategies

The drivers and SDK code samples in this release are compatible with with the publicly available CUDA Toolkit 2.3, follow link to the latest toolkit releases

[Windows] [Linux] [MacOS] 



NVIDIA Drivers for WinXP (190.89)32-bit  64-bit    
NVIDIA Drivers for WinVista and Win7 (190.89)32-bit  64-bit    
NVIDIA Notebook Drivers for WinXP (190.89 Beta)32-bit  64-bit    
NVIDIA Notebook Drivers for WinVista and Win7 (190.89)32-bit  64-bit    
OpenCL Visual Profiler v1.0 Betadownload   Release Notes 
GPU Computing SDK code samples and more32-bit  64-bit   Release Notes 
Best Practices Guide 



NVIDIA Drivers for Linux (190.29)32-bit  64-bit    
OpenCL Visual Profiler v1.0 Beta32-bit  64-bit   Release Notes 
GPU Computing SDK code samples and moredownload   Release Notes 
Best Practices Guide 



OpenCL drivers are released as part of the Mac OS X Showleopard operating system.    
GPU Computing SDK code samples and moredownload   Release Notes 
Best Practices Guide