如何应用GoogleColab的CPU和RAM更大？ [英] How to apply GoogleColab stronger CPU and more RAM?

问题描述

我使用GoogleColab测试数据结构，例如链散列图，探针散列图，AVL树，红黑树，展开树（用Python编写），并且存储非常大的数据集（键值对）借助这些数据结构来测试某些操作的运行时间，其规模就像一个小型的Wikipedia一样，因此运行这些python脚本将占用非常多的内存（RAM），GoogleColab提供了大约12G的RAM，但对我来说还不够，这些python脚本将大约20-30G的RAM，因此当我在GoogleColab中运行python程序时，经常会引发您的程序在12G上限上运行的异常，并经常重新启动。另一方面，我有一些PythonScript做一些递归算法，众所周知，递归算法使用CPU绒毛（以及RAM），当我以20000+递归运行这些算法时，GoogleColab经常无法运行和重启，我知道GoogleColab使用Intel-XEON CPU的两个核心，但是我该如何应用Google提供的更多CPU内核？

I use GoogleColab to test data stuctures like chain-hashmap,probe-hashmap,AVL-tree,red-black-tree,splay-tree(written in Python),and I store very large dataset(key-value pairs) with these data stuctures to test some operation running time,its scale just like a small wikipedia,so run these python script will use very much memory(RAM),GoogleColab offers a approximately 12G RAM but not enough for me,these python scripts will use about 20-30G RAM,so when I run python program in GoogleColab,will often raise an exception that"your program run over 12G upper bound",and often restarts.On the other hand,I have some PythonScript to do some recursion algorithm,as is seen to all,recursion algorithm use CPU vety mush(as well as RAM),when I run these algorithm with 20000+ recursion,GoogleColab often fails to run and restart,I knew that GoogleColab uses two cores of Intel-XEON CPU,but how do I apply more cores of CPU from Google?

推荐答案

最近Google Colab Pro以每月9.99美元的价格推出（2月。 2020）。美国的用户可以获得更高的资源限制，并且可以更频繁地访问更好的资源。

Google Colab Pro recently launched for $9.99 a month (Feb. 2020). Users in the US can get higher resource limits and more frequent access to better resources.

Q& A来自注册页面如下：

Q&A from the signup page is below:

Colab Pro中提供了哪些GPU？

What kinds of GPUs are available in Colab Pro?

使用Colab Pro，您可以优先访问我们最快的GPU。例如，当非订户获得K80时，您可能会访问T4和P100 GPU。您还可以优先访问TPU。但是，Colab Pro中仍然存在使用限制，并且Colab Pro中可用的GPU和TPU的类型可能会随时间而变化。

With Colab Pro you get priority access to our fastest GPUs. For example, you may get access to T4 and P100 GPUs at times when non-subscribers get K80s. You also get priority access to TPUs. There are still usage limits in Colab Pro, though, and the types of GPUs and TPUs available in Colab Pro may vary over time.

在免费版本的Colab中，对更快的GPU，使用限制远低于Colab Pro。

In the free version of Colab there is very limited access to faster GPUs, and usage limits are much lower than they are in Colab Pro.

笔记本可以在Colab Pro中运行多长时间？

How long can notebooks run in Colab Pro?

使用Colab Pro，您的笔记本计算机可以保持长达24小时的连接状态，并且空闲超时相对宽松。但是，不能保证持续时间，并且空闲超时有时可能会有所不同。
在免费版本的Colab笔记本电脑中，笔记本电脑最多可以运行12个小时，并且空闲超时比在Colab Pro中要严格得多。

With Colab Pro your notebooks can stay connected for up to 24 hours, and idle timeouts are relatively lenient. Durations are not guaranteed, though, and idle timeouts may sometimes vary. In the free version of Colab notebooks can run for at most 12 hours, and idle timeouts are much stricter than in Colab Pro.

如何

使用Colab Pro，您可以优先访问高内存VM。这些VM的内存通常是标准Colab VM的两倍，是CPU的两倍。订阅后，您将能够访问笔记本设置以启用高内存VM。此外，有时当Colab检测到您可能需要虚拟机时，可能会自动为其分配高内存VM。但是，不能保证资源，并且对高内存虚拟机有使用限制。

With Colab Pro you get priority access to high-memory VMs. These VMs generally have double the memory of standard Colab VMs, and twice as many CPUs. You will be able to access a notebook setting to enable high-memory VMs once you are subscribed. Additionally, you may sometimes be automatically assigned a high-memory VM when Colab detects that you are likely to need it. Resources are not guaranteed, though, and there are usage limits for high memory VMs.

在免费版本的Colab中，高内存首选项不可用，并且很少会自动为用户分配高内存。内存虚拟机。

In the free version of Colab the high-memory preference is not available, and users are rarely automatically assigned high memory VMs.

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