Nvidia K80 Tensorflow
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Tesla k80 1 windows server 2012 r2 cuda 9 0 b.
Nvidia k80 tensorflow. Python benchmark alexnet py and cuda visible devices 0 python benchmark alexnet py. Gtx 1080 1 windows 7 cuda 9 0 a i. There are still big clusters running these cards but it s debatable whether they are worth the power consumption given that the newer cards deliver so much more performance per watt. Simplep2p p2pbandwidthlatencytest devicequery that all give various kinds of information about p2p peer access capabilities of your system.
It s engineered to boost throughput in real world applications by 5 10x while also saving customers up to 50 for an accelerated data center compared to a cpu only system. I have a question. Tensorflow is an open source software library for numerical computation using data flow graphs. I have a personal machine with a 1080ti.
The warnings you are showing are a result of the configuration of the system that the k80 s are plugged into and not specific to the k80 gpu or tensorflow. The code is deterministic on the same machine. Download drivers for nvidia products including geforce graphics cards nforce motherboards quadro workstations. Both are ran with the same code on github.
Nvidia provides sample codes e g. Nvidia tesla k80 computing card has two gk210 gpus the evaluation tool in object detection seems to currently only use one gpu so i think it s very likely because this is because only one of the two gpus on the k80 is working in this case the calculation performance of the k80 card is equivalent to a down clocked nvidia tesla k20 card single precision floating point performance is only about. The nvidia tesla k80 accelerator dramatically lowers data center costs by delivering exceptional performance with fewer more powerful servers. Nodes in the graph represent mathematical operations while the graph edges represent the multidimensional data arrays tensors that flow between them.
Tesla k80 tesla k40c tesla k40m tesla k40s tesla k40st tesla k40t tesla k20xm tesla k20m. When i first logged in to the machine it asked me to install the drivers and i agreed. I have created a virtual machine in google compute us east 1c region with the following specifications. I run object detection application in tensorflow but k80 inference time is higher than gtx 1080.
I recently started using a tesla k80 on google compute so i can run a lot more trainings. This flexible architecture lets you deploy computation to one or more cpus or gpus in a desktop server or mobile device without rewriting code. The k80 was a workhorse dual gpu card that and the k40 single gpu really established the nvidia platform for compute. N1 standard 2 2 vcpu 7 5 gb memory 1 nvidia tesla k80 gpu boot disk.
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