Google Cloud can preempt GPU (rightmost column), generally cut prices by 40% Still worry about GPU? Today, Google announced that the cloud can seize GPU prices sharply. The price of P100 is $ 0.43 per hour, which is only 2.77 yuan in RMB. Not everyone needs a GPU when working, but for those who need it, the GPU is essential, the more the better. However, GPUs are expensive. Prior to this, Google, Facebook and other giants have carried out a lot of impressive work, and there are many examples of using hundreds or even thousands of GPUs, which are unprecedented. However, as many researchers predict, the price of hardware will continue to decrease. Today, Google announced that the preemptible price of their entire GPU product portfolio has dropped significantly, which is 70% lower than those connected to on-demand GPUs. Earlier this year, the Google Cloud Platform announced that you can connect your GPU to the Preemptible VMs on the Google Compute Engine and Google Kubernetes Engine-Google Cloud Preemptible VMs The fixed fee per hour is only 0.015 USD, which reduces the price of GPU usage by 50%. Today, the price went down another 40%. Google says that preemptible GPUs are ideal for short-term, fault-tolerant and batch workloads, such as machine learning (ML) and high-performance computing (HPC) customers. With preemptible GPUs, you can access large-scale GPU infrastructure at a low, predictable price without having to bid for capacity. The GPU connected to the preemptible virtual machine is basically the same as the on-demand GPU, but there are two important differences: because it is preemptible, the computing engine may stop the service, and you will be warned in advance 30 seconds before stopping the service; You can use them for 24 hours. Any GPU connected to a preemptible virtual machine instance will be considered preemptible and will be billed at a lower price. Now, Google Cloud Platform provides 3 kinds of GPUs, which can be used according to your needs. The GPU price is an hourly rate, and each GPU connected to a virtual machine is charged per second. The prices listed apply to the United States. Prices in other regions may vary. The additional continuous use discount (up to 30%) is only applicable to non-preemptible GPUs. Google is fighting a price war? Many netizens have said that behind this big price cut by Google is the impact on Amazon AWS. Some people speculate that Google introduced TPU 3.0, which replaced a large number of unused GPUs. Some people also speculate that Google has a new product to appear, and reducing the profit margin of the old product market will prevent other companies from making enough profits to invest in R & D and catch up with themselves. In short, in any case, this is a good thing for the general public. How to use cloud preemptible GPU Combined with a custom machine type, a preemptible virtual machine with preemptible GPU allows you to build a computing stack based on the resources you need without the need for other resources. By connecting a preemptible GPU to a custom preemptible virtual machine (VM), you can reduce the amount of GPU VM virtual CPU or host memory. In addition, you can also use preemptible local SSDs and Google's preemptible GPUs for low-cost, high-performance storage options. GPU preemption Innovators, researchers, and scholars who conduct machine learning research have a very high demand for hardware-accelerated infrastructure, and the preemptible GPU has a predictable low price, so the two are well combined. Kayvon Fatahalian, an assistant professor at Stanford University, said: "Preemptible GPUs help our research team use our Scanner open source platform to process large video collections on a large scale. The predictable low cost allows a single graduate student to repeatedly deploy hundreds of GPUs to process Machine learning 100,000 hours of TV news video analysis. This price drop allows us to perform twice the amount of processing on the same budget. " Machine learning training and preemptible GPU Training ML workloads is ideal for using preemptible virtual machines with GPUs. The managed instance groups of Google's Kubernetes engine and computing engine allow you to create dynamically scalable GPU-preemptable virtual machine clusters for large computing jobs. You can use Tensorflow's checkpointing function (checkpointing) to save and restore work progress. start using To start using the preemptible GPU in Google Compute Engine, just add --preemptible to your instance creation command in gcloud, specify scheduling.preemptible as true in the REST API, or preemptive in the Google Cloud Platform Console Set to "On", and then add the GPU as usual. You can use the normal GPU quota to start the preemptible GPU, or you can apply for a special preemptible GPU quota (https://cloud.google.com/compute/quotas), this quota only applies to the connection with the preemptible virtual machine GPU. Inverter Generator,Chetak Gensets Set,Diesel Silent Generator,Silent Diesel Generator Wuxi Doton Power , http://www.dotonpower.com