In addition to Anaconda Notebook’s default runtimes, Anaconda provides access to remote GPU runtimes powered by NVIDIA’s A10 GPUs. These runtimes are ideal for complex, compute-intensive workloads that would otherwise be too time consuming to run in a default environment. You can choose to run the entire notebook on GPU or apply GPU acceleration to specific cells.
Anaconda’s GPU runtime runs a GPU-enabled environment called “anaconda-01 - nvidia-a10”. This environment contains the libraries, drivers, and configurations necessary for communicating with NVIDIA GPUs, as well as the ipykernel package to enable interactive computing in Python. See below for a list of all packages included in the default environment.
When you assign a GPU runtime to a notebook (or notebook cell), you’re using the default GPU-enabled environment. For more information about runtimes and environments, see Runtimes.
At this time, Anaconda is offering free credits to select paid subscribers only. Free tier subscribers who would like to use GPU runtimes can upgrade to gain access.
Once you assign a GPU runtime to a notebook or cell, you can run your code as you normally would. You should notice a considerable increase in processing speed, especially for more complex tasks.
Anaconda’s default GPU runtime, “anaconda-01 - nvidia-a10”, is tied to a read-only, GPU-enabled environment that includes the latest Anaconda, AI, and NVIDIA packages.
Because cells assigned a GPU runtime run in a separate environment from the rest of the notebook, variables must be transferred between the cell and the notebook to ensure they are accessible in both runtimes.
Follow these steps to transfer variables:
Click Variable transfer beside a cell with a GPU runtime assigned.
Enter the inputs and/or outputs to be transferred between the notebook and cell runtimes.
Click Set variables.
The inputs and/or outputs can now be used in the GPU runtime cell and notebook.
When you assign a GPU runtime to a notebook, you are asked to reserve a defined number of minutes to use toward the notebook’s GPU execution time. Reserved time is calculated in credits, with one credit equaling 100 real-world seconds.
Once the notebook launches, the reserved time starts to count down. The reserved time continues to count down both when running code and when the notebook is idle.
Track how much reserved time is left by hovering over the top-right countdown bar:
When your reserved time drops below five minutes (300 seconds), the countdown bar turns red. Once the reserved time hits zero, the GPU runtime session automatically terminates.
Anaconda recommends conserving your GPU usage by either assigning a GPU runtime to individual cells that require higher compute power rather than the entire notebook, or waiting to assign the GPU runtime until you’re ready to run your code, and then stopping the GPU runtime session as soon as the code has executed.
There are multiple ways you can stop a GPU runtime session:
Select Kernels from the top menu bar.
Select Shut Down All to shut down all runtimes.
In the confirmation dialog, click Shut Down All.
Select Kernels from the top menu bar.
Select Shut Down All to shut down all runtimes.
In the confirmation dialog, click Shut Down All.
In a notebook with an assigned GPU runtime, click the top-right countdown bar.
On the Runtime home page, click Delete Runtime next to the runtime you’d like to shut down.
View your GPU usage stats and remaining credits on the Runtime home page. Select More on Usage to view additional details:
The Overview page shows your running GPU runtimes, remaining credits, and historical credit consumption.
The History page shows your usage history, including GPU session runtime names, types, start date, end date, credits used, and session duration.
The Reservations page shows any currently running GPU runtimes, the credits assigned to the reservation session, and the reservation start and end times.
Anaconda offers credits to access GPU compute time. One credit equals 100 real-world seconds. Note that this is different from how high-compute seconds are calculated for CPU use.
Credits are automatically deducted as reserved time is used. For example, if you use 10 minutes of reserved time, 6.00 credits will be deducted from your account.
View your remaining credits on the Usage Overview page.
At this time, Anaconda is offering 500 free credits to select paid subscribers only. See note for details on upgrading your subscription to gain access.
Reload the Anaconda Notebooks page and then click “Launch a Remote Runtime” from the Launcher. If you’re still unable to run a GPU runtime, file a support ticket.
