👁️ Overview
The STFC Cloud provides a number of flavors to users but these fall into 4 categories at the moment.
No flavor has resilient storage. If this is required you should boot from Volume at VM creation time
Note: our flavors are created in such a way that they will efficiently pack onto the hardware we have - due to this we cannot create additional flavors on demand as that may lead to scheduling difficulties under heavy utilisation.
🖥️ Compute flavors
l flavors
(e.g. l3.nano, l2.xsmall)
These are flavors which utilize local SSD storage on the hypervisors with all of the storage being allocated to the root disk. Larger l flavors may struggle to live migrate due to capacity availability and disk image sizes so where possible be sure that you can recreate your machines using other methods, such as configuration management.
le flavors
(e.g. le3.small, le2.medium)
These are flavors which utilize local SSD storage on the hypervisors with 100GB being allocated to the root disk and the rest to an ephemeral disk. Larger le flavors may struggle to live migrate due to capacity availability and disk image sizes so where possible be sure that you can recreate your machines using other methods, such as configuration management.
Compute flavor list
Name | RAM (MB) | Disk (GB) | Ephemeral Disk (GB) | VCPUs |
---|---|---|---|---|
l3.nano | 8,192 | 50 | 0 | 2 |
l3.micro | 16,384 | 100 | 0 | 4 |
l2.tiny | 30,720 | 200 | 0 | 8 |
l3.tiny | 30,720 | 200 | 0 | 8 |
l2.xsmall | 61,440 | 400 | 0 | 16 |
l3.xsmall | 61,440 | 400 | 0 | 16 |
le2.small | 125,952 | 100 | 700 | 30 |
le3.small | 125,952 | 100 | 700 | 30 |
l2.small | 125,952 | 800 | 0 | 30 |
l3.small | 125,952 | 800 | 0 | 30 |
le2.medium | 250,880 | 100 | 1500 | 60 |
le3.medium | 250,880 | 100 | 1500 | 60 |
l2.medium | 250,880 | 1600 | 0 | 60 |
l3.medium | 250,880 | 1600 | 0 | 60 |
le2.large | 501,760 | 100 | 3100 | 124 |
le3.large | 501,760 | 100 | 3100 | 124 |
l2.large | 501,760 | 3200 | 0 | 124 |
l3.large | 501,760 | 3200 | 0 | 124 |
💪 GPU flavors
GPU flavors are not available by default and capacity is limited. To request access please contact STFC cloud support.
g flavors
(e.g. g-a100.x1, g-rtx4000.x4)
These have the same CPU configuration as l*.* flavors but have a GPU attached:
g-rtx4000.* have one or more NVidia Quadro RTX 4000 cards attached (the smallest has 1, the largest has 4)
g-rtx4000-ref.* have one or more NVidia Quadro RTX 4000 cards attached (the smallest has 1, the largest has 4)
These are older, out of warranty nodes which have been refitted with new GPUs. For this reason these are primarily reserved for short term use such as training courses. If you have a use case you want to use these for then please get in touch with cloud support.
g-a4000.* have one or more NVidia RTX A4000 cards attached (the smallest has 1, the largest has 4)
g-a4000-ref.* have one or more NVidia RTX A4000 cards attached (the smallest has 1, the largest has 4)
These are older out of warranty nodes which have been refitted with new GPUs. For this reason these are primarily reserved for short term use such as training courses. If you have a use case you want to use these for then please get in touch with support.
g-v100.* have one or more NVidia Tesla V100 32GB cards attached (the smallest has 1, the largest has 4)
g-a100.* have one or more NVidia Tesla A100 40GB cards attached (the smallest has 1, the largest has 4)
g-a100-n100.* have one or more NVidia Tesla A100 40GB cards attached (the smallest has 1, the largest has 4) with higher core count and more network bandwidth
These are currently reserved for specific projects.
g-a100-80gb.* have one or more NVidia Tesla A100 80GB cards attached (the smallest has 1, the largest has 8)
g-arc-a770.* have one or two Intel Arc A770 16GB cards
These are very limited in number and are primarily in place for prototyping.
g-amd-w6600.* have one or more AMD W6600 8GB cards (the smallest has 1, the largest has 4)
These are very limited in number and are primarily in place for prototyping.
f flavors
(e.g. f-xilinxu200.x1)
These are similar to the g* flavors but have fpga accelerators rather than GPUs
f-xilinxu200.* have one or more Xilinx U200 FPGA cards
These are very limited in number
GPU flavor list
Name | RAM (MB) | Disk (GB) | VCPUs | GPU(s) |
---|---|---|---|---|
g-a4000-ref.x1 | 91,200 | 700 | 12 | 1 x A4000 |
g-a4000.x1 | 122,880 | 400 | 16 | 1 x A4000 |
g-a4000.x2 | 245,760 | 800 | 32 | 2 x A4000 |
g-a4000.x4 | 491,520 | 1600 | 60 | 4 x A4000 |
g-a4000.x8 | 983,040 | 3200 | 124 | 8 x A4000 |
g-rtx4000.x1 | 92,160 | 700 | 12 | 1 x RTX4000 |
g-rtx4000.x2 | 184,320 | 1400 | 28 | 2 x RTX4000 |
g-rtx4000.x4 | 358,400 | 2800 | 60 | 4 x RTX4000 |
g-rtx4000-ref.x1 | 921,600 | 700 | 12 | 1 x RTX4000 |
g-a100.x1 | 102,400 | 1600 | 12 | 1 x A100 40GB |
g-a100.x2 | 204,800 | 3200 | 28 | 2 x A100 40GB |
g-a100.x4 | 460,800 | 6400 | 60 | 4 x A100 40GB |
g-a100.x1hm | 204,800 | 1600 | 12 | 1 x A100 40GB |
g-a100.x2hm | 460,800 | 3200 | 30 | 2 x A100 40GB |
g-a100.x4hm | 870,400 | 6400 | 60 | 4 x A100 40GB |
g-a100-n100.x1 | 102,400 | 800 | 30 | 1 x A100 40GB |
g-a100-n100.x2 | 225,280 | 1600 | 60 | 2 x A100 40GB |
g-a100-n100.x4 | 450,560 | 3200 | 124 | 4 x A100 40GB |
g-a100-80gb.x1 | 102,400 | 800 | 30 | 1 x A100 80GB |
g-a100-80gb.x2 | 225,280 | 1600 | 60 | 2 x A100 80GB |
g-a100-80gb.x4 | 450,560 | 3200 | 124 | 4 x A100 80GB |
g-a100-80gb-2022.x1 | 122,880 | 400 | 16 | 1 x A100 80GB |
g-a100-80gb-2022.x2 | 245,760 | 800 | 32 | 2 x A100 80GB |
g-a100-80gb-2022.x4 | 491,520 | 1600 | 60 | 4 x A100 80GB |
g-a100-80gb-2022.x8 | 983,040 | 3200 | 124 | 8 x A100 80GB |
g-v100.x1 | 76,800 | 700 | 12 | 1 x v100 |
g-v100.x2 | 174,080 | 1400 | 28 | 2 x v100 |
g-v100.x4 | 358,400 | 2800 | 60 | 4 x v100 |
g-arc-a770-ref.x1 | 158,720 | 1400 | 28 | 1 x Intel Arc A770 |
g-amd-w6600-ref.x1 | 92,160 | 700 | 12 | 1 x AMD w6600 |
f-xilinxu200.x1 | 57,344 | 400 | 16 | 1 x Xilinx U200 |
🕸️ Deprecated flavors
c flavors
(e.g. c2.xlarge, c3.small)
C flavors are now deprecated and new VMs will not be able to be created after the 12th of April 2023. It is recommend to use l flavors instead.
These are flavors with dedicated CPU cores meaning that a VCPU core assigned to your VM is dedicated to you.
These flavors are great for computation and are optimised to either be within a single NUMA node providing great performance or balanced equally across the NUMA nodes in the hypervisor.
📚 Related articles
Reviewer | Review period |
---|---|
| 6 months |