13.01.2020

New Cuda Driver 6.0.37 For Mac

New Cuda Driver 6.0.37 For Mac Os X
New Cuda Driver 6.0.37 For Mac
New Cuda Driver 6.0.37 For Mac Os

212 kH/s with CUDA 5.5.47 and Web drivers 331.01.01f02 Struggles to pass 141kH/s with CUDA 6.0.37 and drivers 331.01.01f02. Installing 5.5.47 back pushes benchmark up to 169 kH/s but won't go back to figures from before installation, something somewhere has been overwritten, maybe reboot required. CUDA 6 Production Release. Note: * Includes ARMv7 cross-complilation and profiling tools. Download English (India) drivers for NVIDIA hardware -,,, New Release 6.0.37. CUDA driver 6.0.37 is required for CUDA support on Mac OS X 10.9 Mavericks. CUDA Drivers for MAC Archive. AI AND DEEP LEARNING. CUDA ACCELERATED COMPUTING. CUDA 6.0.37 driver for MAC Release Date: CUDA 5.5.47 driver for MAC Release Date: CUDA 5.5.28 driver for MAC Release Date: CUDA 5.5.25 driver for MAC. Download English (U.S.) drivers for NVIDIA hardware -,,, New Release 6.0.37. CUDA driver 6.0.37 is required for CUDA support on Mac OS X 10.9 Mavericks.

Freeware

macOS

1.3 GB

I just installed a Quadro 4000 (for Mac) in my MacPro 4,1 Quad Core Xeon, 12GB RAM, running Lion 10.7.5. Updated drivers - both Nvidia and CUDA, but have no CUDA GPU accelaration.

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Features:

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C/C++ compiler
Visual Profiler
GPU-accelerated BLAS library
GPU-accelerated FFT library
GPU-accelerated Sparse Matrix library
GPU-accelerated RNG library
Additional tools and documentation

Features:

Easier Application Porting
Share GPUs across multiple threads
Use all GPUs in the system concurrently from a single host thread
No-copy pinning of system memory, a faster alternative to cudaMallocHost()
C++ new/delete and support for virtual functions
Support for inline PTX assembly
Thrust library of templated performance primitives such as sort, reduce, etc.
Nvidia Performance Primitives (NPP) library for image/video processing
Layered Textures for working with same size/format textures at larger sizes and higher performance
Faster Multi-GPU Programming
Unified Virtual Addressing
GPUDirect v2.0 support for Peer-to-Peer Communication
New & Improved Developer Tools
Automated Performance Analysis in Visual Profiler
C++ debugging in CUDA-GDB for Linux and MacOS
GPU binary disassembler for Fermi architecture (cuobjdump)
[Parallel Nsight 2.0](http://developer.nvidia.com/nvidia-parallel-nsight) now available for Windows developers with new debugging and profiling features.

Install Instructions:

Windows

Double click cuda_9.0.176_win10_network.exe
Follow on-screen prompts

macOS

Open cuda_9.0.176_mac_network.dmg
Launch the installer
Follow the on-screen prompts

Fedora

`sudo rpm -i cuda-repo-fedora25-9-0-local-9.0.176-1.x86_64.rpm`
`sudo dnf clean all`
`sudo dnf install cuda`

OpenSUSE

`sudo rpm -i cuda-repo-opensuse422-9-0-local-9.0.176-1.x86_64.rpm`
`sudo zypper refresh`
`sudo zypper install cuda`

Ubuntu 17.04

`sudo dpkg -i cuda-repo-ubuntu1704-9-0-local_9.0.176-1_amd64.deb`
`sudo apt-key add /var/cuda-repo-<version>/7fa2af80.pub`
`sudo apt-get update`
`sudo apt-get install cuda`

Ubuntu 16.04

`sudo dpkg -i cuda-repo-ubuntu1604-9-0-local_9.0.176-1_amd64.deb`
`sudo apt-key add /var/cuda-repo-<version>/7fa2af80.pub`
`sudo apt-get update`
`sudo apt-get install cuda`