是否有适用于Windows的Nvidia Grid M40驱动程序

您可以尝试标准的quadro / grid（通用）驱动程序（来自标准下载位置http://www.nvidia.com/Download/index.aspx?lang=en-us  - >“GRID” - >“GRID系列” - >
...  - > 376.33-quadro-grid-desktop-notebook-win8-win7-64bit-international-whql.exe）并尝试编解码器SDK。
（更新：我期待nv_dispwi.inf，但驱动程序包中缺少对GRID M40和Tesla M10的支持。）
我的观点：NVidia否认存在GRID M40板（从不设计，制造，销售或支持，但请查看Ebay）。
HPE删除有关产品的所有痕迹，部件号为“J0X20A 796120-001 797638-001”。
该卡的新版本（带有新的双倍尺寸内存芯片）标有“Tesla M10”（https://gridforums.nvidia.com/default/topic/823/grid-boards/tesla-m10/），它的不同之处在于“
pci subsystem id“。



以下为原文

You can try standard quadro/grid (universal) driver (from standard download location http://www.nvidia.com/Download/index.aspx?lang=en-us -> "GRID" -> "GRID Series" -> ... -> 376.33-quadro-grid-desktop-notebook-win8-win7-64bit-international-whql.exe) and try Codec SDK. (Update: I look to nv_dispwi.inf but support for GRID M40 and Tesla M10 are missing in driver package.)

My opinion: NVidia deny existence of GRID M40 board (never design, build, sell or support, but check Ebay). HPE delete all traces about product with part numbers "J0X20A 796120-001 797638-001". New release of this card (with new double sized memory chip) is branded "Tesla M10" (https://gridforums.nvidia.com/default/topic/823/grid-boards/tesla-m10/) and it differs in "pci subsystem id".

我已经尝试过每一个驱动程序，有一个驱动程序在ebay上有一个卖家，他在Windows中使用了M40的屏幕截图。
上帝知道哪个版本虽然我试图传达没有运气。
是的，Nvidia的无知一再表示没有这样的卡，该卡在Linux中使用Compute的标准驱动程序我在安装CentOS的过程中看到。
在纸张上计算的伟大卡，双插槽外形中的低功耗绘制四核gpu。
具有视频编码IMO的巨大潜力。



以下为原文

I have tried every driver, There is a driver that works there was a seller on ebay who had a screenshot of the M40 being used in Windows. God knows which version though i tried to message with no luck.

Yes the ignorance of Nvidia repeatedly saying there is no such card, The card works in Linux with standard drivers for Compute I'm in the process of install CentOS to see.

Great card for compute on paper, Low power draw quad gpu in a dual slot form factor. Has great potential for Video Encoding IMO.

GM107的编码性能不佳（只有一个编码器引擎和Maxwell Gen1），即使对于GPU H.264加速64xVDI（M10变体，作为营销荣耀）它也是不合适的。
反思：
1x GRID M40 ==特斯拉M10是带有一个编码器引擎的4xGM107（Maxwell Gen1） - 用于编码~235 FPS（低通道，高通道，1920x1080，YUV4：2：0,8位） -  4 * 235~940 FPS / 225W / 2
slot / 4 * 5 = 20 SMM = 2560 CUDA核心
1x Quadro M5000是GM204（Maxwell Gen2），带有两个编码器引擎 - 用于编码~361 FPS（低通，高通，1920x1080，YUV4：2：0,8位） -  2 * 361~722 FPS / 150W / 2插槽/ 16 SMM
= 2048个CUDA核心
1x Quadro M4000是带有两个编码器引擎的GM204（Maxwell Gen2） - 用于编码~361 * 80％FPS（低通，高通，1920x1080，YUV4：2：0,8位） -  2 * 361 * 80％~578 FPS（ -
由于降频而估计性能下降20％/ 120W / 1插槽/ 13 SMM = 1664 CUDA内核
2x Quadro M4000  -  2 * 2 * 361 * 80％~1155 FPS / 240W / 2插槽/ 2 * 13 SMM = 3328 CUDA核心 - 似乎是更好的支持解决方案（FPS + 20％，功率+ 7％，价格
+ 30％（Quadro M4000（ebay / new）~2x $ 650 = $ 1300，GRID M40（ebay）〜$ 1000））
1x Quadro P5000是带有两个编码器引擎的GP104（Pascal） - 用于编码~535 FPS（低通，高通，1920x1080，YUV4：2：0,8位） -  2 * 535~1070 FPS / 180W / 2插槽（+ 8k HEVC）
和10位编码）/ 20个SMM = 2560个CUDA核心
1x特斯拉P4是带有两个编码器引擎的GP104（Pascal） - 用于编码~535 * 70％FPS（低通，高通，1920x1080，YUV4：2：0,8位） -  2 * 535 * 70％~749 FPS（-30）
由于低频估计性能下降百分比）/ 50-75W / 1插槽（+ 8k HEVC和10bit编码）（FPS -20％，功率-66％，价格+ 80％）/ 20 SMP = 2560 CUDA核心
2x特斯拉P4  -  2 * 2 * 535 * 70％~1498 FPS / 100-150W / 2插槽/ 2 * 20 SMP = 5120 CUDA内核（FPS + 60％，功率-33％，价格+ 260％）
NVidia应该披露更详细的编码器/解码器基准（依赖于时钟速度（和突发）和内存带宽）。
参考文献：
https://developer.nvidia.com/video-encode-decode-gpu-support-matrix
https://developer.nvidia.com/nvidia-video-codec-sdk#NVENCFeatures
https://developer.nvidia.com/nvenc-application-note



以下为原文

Encoding performance of GM107 is not good (only one encoder engine and Maxwell Gen1) and it is unsuitable even for GPU H.264 accelerated 64xVDI (M10 variant, as marketing glorify). Rethink:

• 1x GRID M40 == Tesla M10 is 4xGM107 (Maxwell Gen1) with one encoder engine - for encoding ~ 235 FPS (lowlat, highperf, 1920x1080, YUV4:2:0, 8 bit) - 4*235 ~ 940 FPS / 225W / 2 slots / 4*5=20 SMM = 2560 CUDA cores
  
• 1x Quadro M5000 is GM204 (Maxwell Gen2) with two encoder engines - for encoding ~ 361 FPS (lowlat, highperf, 1920x1080, YUV4:2:0, 8 bit) - 2*361 ~ 722 FPS / 150W / 2 slots  / 16 SMM = 2048 CUDA cores
  
• 1x Quadro M4000 is GM204 (Maxwell Gen2) with two encoder engines - for encoding ~ 361*80% FPS (lowlat, highperf, 1920x1080, YUV4:2:0, 8 bit) - 2*361*80% ~ 578 FPS (-20% performance drop estimated due to underclocking) / 120W / 1 slot / 13 SMM = 1664 CUDA cores
  
• 2x Quadro M4000 - 2*2*361*80% ~ 1155 FPS / 240W / 2 slots / 2*13 SMM = 3328 CUDA cores - It seems to be better and supported solution (FPS +20%, power +7%, price +30% (Quadro M4000 (ebay/new) ~ 2x$650=$1300, GRID M40 (ebay) ~ $1000))
  
• 1x Quadro P5000 is GP104 (Pascal) with two encoder engines - for encoding ~ 535  FPS (lowlat, highperf, 1920x1080, YUV4:2:0, 8 bit) - 2*535 ~ 1070 FPS / 180W / 2 slots (+ 8k HEVC and 10bit encoding) / 20 SMM = 2560 CUDA cores
  
• 1x Tesla P4 is GP104 (Pascal) with two encoder engines - for encoding ~ 535*70%  FPS (lowlat, highperf, 1920x1080, YUV4:2:0, 8 bit) - 2*535*70% ~ 749 FPS (-30% performance drop estimated due to underclocking) / 50-75W / 1 slot (+8k HEVC and 10bit encoding)(FPS -20%, power -66%, price +80%) / 20 SMP = 2560 CUDA cores
  
• 2x Tesla P4 - 2*2*535*70% ~ 1498 FPS / 100-150W / 2 slots / 2*20 SMP = 5120 CUDA cores (FPS +60%, power -33%, price +260%)
  

NVidia should disclosure more detailed encoder/decoder benchmarks (with dependency on clock speed (and burst) and memory bandwidth).

Refs:
https://developer.nvidia.com/video-encode-decode-gpu-support-matrix
https://developer.nvidia.com/nvidia-video-codec-sdk#NVENCFeatures
https://developer.nvidia.com/nvenc-application-note

我同意上述情况，并感谢您的努力，尽管其中列出的其他成本低于50％，它提供了巨大的价值（我得到了400美元），计算下的最大功耗也是130瓦总计，如STH所述。
我们使用的编码器与NVENCODE略有不同，有多种效果可以很好地利用cuda和Resolve。
Card正在使用Nvidia驱动程序开发CentOS。
Resolve正在查看所有4张牌。
现在要获得Windows计算驱动程序？



以下为原文

I agree with the above and thanks for the effort although at less than 50% the cost of the others listed it offers great value (I got it for $400us), Also max power draw under compute is 130w Total as documented at STH.

Also the encoder we use is a little different to NVENCODE, There are effects that utilise cuda and Resolve scales well with multi gpu.

Card is working on CentOS with Nvidia Drivers. Resolve is seeing all 4 cards.

Now to get windows compute drivers??