Compute profile configuration options

Options for configuring the compute profile of a cloud environment.

Prior reading: Overview of Cloud Environments

Purpose: This document provides detailed instructions for customizing the compute resources allocated to a cloud environment through the web UI.

Types of processors

CPU — Central Processing Unit

The central processing unit (CPU), or simply processor, can be considered the “brain” of a computer. Every computational machine will have at least one CPU, which is connected to every part of the computer system. It’s the operational center that receives, executes, and delegates the instructions received from programs. CPUs also handle computational calculations and logic. Increasing the number of CPUs accelerates the processing of these tasks. Other types of processors (GPUs or TPUs) may be better suited for processing specialized tasks, such as parallel computing and machine learning.

GPU — Graphical Processing Unit

A graphical processing unit (GPU) is a specialized processor that excels at parallel computing, which means processing many tasks at once. While a central processing unit (CPU) must process tasks one by one, a GPU can split complex tasks into many pieces and work through them simultaneously. GPUs were traditionally used to accelerate video rendering, but their parallel computing ability also makes them ideal for tasks such as sequence alignment, AI and machine learning.

  • GPUs may not be available for all environment images.
  • Use of GPUs will increase the running cost of a VM per hour. This makes it particularly important to STOP a GPU-enabled environment while you’re not using it.

You can read about GPUs on Google Compute Engine in more depth here, and see more detail about GPU pricing here.


Memory, also known as random access memory (RAM), is where programs and data that are currently in use are temporarily stored. The central processing unit (CPU) receives instructions & data from programs, which is kept in the computer’s memory while being used. Once the instructions are completed, or the program is no longer in use, the memory is freed up. If the computer system doesn’t have enough memory for all of the CPU’s instructions, the system’s performance will diminish and slow down. While the CPU is commonly thought of as a computer’s brain, you can think of memory as the attention span.

Last Modified: 16 November 2023