The following command will show you the current memory usage in Jupyter Notebook: `%system free -m` For example, the following command will show you the current CPU usage in Jupyter Notebook: `%system top -b -n 1 | grep Cpu` In Jupyter Notebook, you can monitor CPU and memory usage by using the %system magic command. Once you are on the compute node, run either ps or top. The easiest way to check the instantaneous memory and CPU usage of a job is to ssh to a compute node your job is running on. If your job is already running, you can check on its usage, but will have to wait until it has finished to find the maximum memory and CPU used. It also helps to ensure that the system has enough memory resources available to handle peak loads and avoid swapping, which can slow down the system.īy monitoring CPU and Memory usage, administrators can proactively identify and resolve performance issues, avoid system crashes, and ensure a stable and efficient system.Īdministrators can also make sure your jobs use the right amount of RAM and the right number of CPUs helps you and others using the clusters use these resources more effeciently, and in turn get work done more quickly. Memory usage: Monitoring memory usage helps to identify memory leaks, which are a common cause of system crashes and instability. It also helps to detect potential security issues such as malware or rogue processes that consume a high amount of CPU resources. Monitoring CPU (Central Processing Unit) and Memory usage is important in order to ensure the performance and stability of a system.ĬPU usage: Monitoring CPU usage helps to identify performance bottlenecks, such as CPU-intensive processes, that may slow down the system.

Linux monitor cpu usage