Virtual Machine Sizes and Configurations¶
Jetstream2 can be used in several different virtual machine (VM) sizes which are charged in service units (SUs) based on how much of the total system resource is used.
The basic unit of VM allocation for Jetstream is based on a virtual CPU (vCPU) hour: 1 service unit (SU) is equivalent to 1 vCPU for 1 hour of wall clock time. The table below outlines the VM sizes created for Jetstream2.
Jetstream2 Resources
Please note that these are all separate resources under ACCESS. You must select Jetstream2 (CPU), Jetstream2 GPU or Jetstream2 Large Memory when spending credits to have access to these JS2 resources. Having access to one does NOT yield access to all.
While the root disk sizes here are fixed, there is an option called “boot from volume” that will allow you to specify a larger root disk using quota from your storage allocation. Instructions for that are in the user interface sections.
Jetstream2 CPU¶
VM Size | vCPUs | RAM (GB) | Local Storage (GB) | SU cost per hour |
---|---|---|---|---|
m3.tiny | 1 | 3 | 20 | 1 |
m3.small | 2 | 6 | 20 | 2 |
m3.quad | 4 | 15 | 20 | 4 |
m3.medium | 8 | 30 | 60 | 8 |
m3.large | 16 | 60 | 60 | 16 |
m3.xl | 32 | 125 | 60 | 32 |
m3.2xl | 64 | 250 | 60 | 64 |
m3.3xl* | 128 | 500 | 60 | 128 |
* m3.3xl will not be available by default. It will only be available by request and with proper justification
Jetstream2 Large Memory¶
Jetstream2 Large Memory nodes charge 2 SUs per vCPU hour or 2 SUs per core per hour.
VM Size | vCPUs | RAM (GB) | Local Storage (GB) | SU cost per hour |
---|---|---|---|---|
r3.large | 64 | 500 | 60 | 128 |
r3.xl | 128 | 1000 | 60 | 256 |
Jetstream2 GPU¶
Jetstream2 GPU nodes charge 4 SUs per vCPU hour or 4 SUs per core per hour. Additionally, there are four NVIDIA A100 GPUs on each node. These GPUs are subdivided using NVIDIA virtual GPU (vGPU) into up to fractions of the A100 to allow more researchers and students to make use of the GPU resource.
5 GPU slices = 1 NVIDIA 40GB Ampere A100 GPU
VM Size | vCPUs | RAM(GB) | Local Storage (GB) | GPU Portion/GPU Ram | SU cost / hour |
---|---|---|---|---|---|
g3.small | 4 | 15 | 60 | 20% of GPU / 5gb RAM | 16 |
g3.medium | 8 | 30 | 60 | 25% of GPU / 10gb RAM | 32 |
g3.large | 16 | 60 | 60 | 50% of GPU / 20gb RAM | 64 |
g3.xl | 32 | 125 | 60 | 100% of GPU / 40gb RAM | 128 |
Note: If you are using a portion of the GPU and the rest of the GPU is idle, you may see higher utilization
This flavor information may be subject to changes in the future.
Example of SU estimation:¶
Note: You can now estimate your SU needs using the usage estimation calculator here: Usage Estimation Calculator
- First determine the VM resource appropriate to your needs (CPU only, large memory, GPU):
- If your work requires 24 GB of RAM and 60 GB of local storage:
- you would request 8 SUs per hour to cover a single m3.medium VM instance.
- If your work requires 10 GB of local storage in 1 core using 3 GB of RAM:
- you would request 2 SUs per hour for an m3.small VM instance.
- If your work requires 1TB of RAM:
- you would request 256 SUs per hour for an r3.xl instance on Jetstream Large Memory
- If you work requires 20gb of GPU RAM:
- you would request 64 SUs per hour for a g3.large instance on Jetstream GPU
- If your work requires 24 GB of RAM and 60 GB of local storage:
- You then would calculate for the appropriate resource (refer to the tables above):
- For Jetstream2 CPU, you would then multiply by the number of hours you will use that size VM in the next year and multiply by the number of VMs you will need.
- For Jetstream2 Large Memory and GPU, either refer to the SU cost per hour in the last column, or multiply hours times 2 for LM or 4 for GPU
- To calculate the number of SUs you will need in the next year, first estimate the number of hours you expect to work on a particular project. For example, if you typically work 40 hours per week and expect to spend 25% of your time on this project that would be 10 hours per week.
- Next, calculate the total number of hours per year for this project:
- Total hours = 10 hours per week * 52 weeks per year
- Total hours = 520
- Finally, calculate the total SUs for the year for a single VM instance:
- Total SUs = 520 hours per year * vCPUs
- e.g. For a Medium VM instance: Total SUs = 520 hours per year * 8vCPUs
- Total SUs = 4160
- Total SUs = 520 hours per year * vCPUs
- If your project requires more than 1 VM instance, multiply the total SUs by the number of VMs that you will need:
- Total SUs needed for 3 medium size VMs = 3 * 4160
- Total SUs = 12480
The calculations above assume that your VM is shutdown properly. For instructions see:
- Cacao instance management actions
- Exosphere instance management actions
- Horizon instance management actions
- Command line instance management actions
SU Estimation for Infrastructure or “Always On” allocations¶
For jobs that may need to run for extended periods or as “always on” infrastructure, you can take this approach:
VM cost (SUs) x 24 hours/day x 365 days = single VM cost per year
or as an example for each resource, an m3.large, r3.large, and g3.large each running for a year:
m3.large (16 cores) x 24 hours/day x 365 days = 140,160 SUs
r3.large (64 cores x 2 SUs/hour) x 24 hours/day x 365 days = 1,121,280 SUs
g3.large (16 cores x 4 SUs/hour) x 24 hours/day x 365 days = 560,640 SUs