MIG: Difference between revisions

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+-----------------------------------------------------------------------------+
+-----------------------------------------------------------------------------+
</syntaxhighlight>
</syntaxhighlight>
== Enable MIG Mode ==
List the possible placements available using the following command
When MIG is enabled on the GPU, depending on the GPU product, the driver will attempt to reset the GPU so that MIG mode can                          take effect.                                         <syntaxhighlight lang="bash">
$ sudo nvidia-smi -pm 1    # persistence mode is required to enable MIG
Enabled Legacy persistence mode for GPU 00000000:4F:00.0.
All done.


== Enable MIG Mode ==
$ sudo nvidia-smi -mig 1   # Enable MIG
When MIG is enabled on the GPU, depending on the GPU product, the driver will attempt to reset the GPU so that MIG mode can                          take effect.                                                     
Enabled MIG Mode for GPU 00000000:4F:00.0
All done.
<kbd>$ sudo nvidia-smi -i 0 -mig 1</kbd>
Enabled MIG Mode for GPU 00000000:36:00.0
All done.
if encounter a message saying “Warning: MIG mode is in pending enable state for GPU XXX:XX:XX.X:In use by another client …”, when enabling MIG. you need to stop '''nvsm''' and '''dcgm''', then try again.<ref>https://docs.nvidia.com/datacenter/tesla/mig-user-guide/</ref>


#Verify enabled MIG mode
$ nvidia-smi --query-gpu=pci.bus_id,mig.mode.current --format=csv           
pci.bus_id, mig.mode.current
00000000:4F:00.0, Enabled
</syntaxhighlight>If encounter a message saying “Warning: MIG mode is in pending enable state for GPU XXX:XX:XX.X:In use by another client …”, when enabling MIG. you need to stop '''nvsm''' and '''dcgm''', then try again.<ref>https://docs.nvidia.com/datacenter/tesla/mig-user-guide/</ref>
  $ sudo systemctl stop nvsm
  $ sudo systemctl stop nvsm
  $ sudo systemctl stop dcgm
  $ sudo systemctl stop dcgm
  $ sudo nvidia-smi -i 0 -mig 1
  $ sudo nvidia-smi -i 0 -mig 1
 
<kbd>$ nvidia-smi -i 0 --query-gpu=pci.bus_id,mig.mode.current --format=csv</kbd>
pci.bus_id, mig.mode.current 
00000000:36:00.0, Enabled
<nowiki>**</nowiki> Reference [https://docs.nvidia.com/datacenter/tesla/mig-user-guide/ MIG user guide] for various post processing of MIG configuration change to take effect.
<nowiki>**</nowiki> Reference [https://docs.nvidia.com/datacenter/tesla/mig-user-guide/ MIG user guide] for various post processing of MIG configuration change to take effect.


== List GPU Instance Profiles ==
== List GPU Instance Profiles ==
List the possible placements available using the following command. it would be helpful to review [https://cloud.redhat.com/blog/using-nvidia-a100s-multi-instance-gpu-to-run-multiple-workloads-in-parallel-on-a-single-gpu performance of different MIG instance size] using [[MLPerf]] with Single Shot MultiBox Detector (SSD) training [[benchmark]].   
List the possible placements available using the following command. it would be helpful to review [https://cloud.redhat.com/blog/using-nvidia-a100s-multi-instance-gpu-to-run-multiple-workloads-in-parallel-on-a-single-gpu performance of different MIG instance size] using [[MLPerf]] with Single Shot MultiBox Detector (SSD) training [[benchmark]].   
  <kbd>$ nvidia-smi mig -lgipp</kbd>
The syntax of the placement is {<index>}:<GPU Slice Count> and shows the placement of the instances on the GPU <syntaxhighlight lang="bash">
GPU  0 Profile ID 19 Placements: {0,1,2,3,4,5,6}:1 #seven instances of <samp>1g.5gb</samp> (profile ID 19)
#H100 NVL, list possible placements
GPU  0 Profile ID 20 Placements: {0,1,2,3,4,5,6}:1  
#The syntax of the placement output is {<index>}:<GPU Slice Count> and shows the placement of the instances on the GPU
GPU  0 Profile ID 15 Placements: {0,2,4,6}:2
$ nvidia-smi mig -lgipp
GPU  0 Profile ID 14 Placements: {0,2,4}:2
GPU  0 Profile ID 19 Placements: {0,1,2,3,4,5,6}:1
GPU  0 Profile ID  9 Placements: {0,4}:4.    #create two instances of type <samp>3g.20gb</samp> (profile ID 9)
GPU  0 Profile ID 20 Placements: {0,1,2,3,4,5,6}:1
GPU  0 Profile ID  5 Placement : {0}:4
GPU  0 Profile ID 15 Placements: {0,2,4,6}:2
GPU  0 Profile ID  0 Placement : {0}:8
GPU  0 Profile ID 14 Placements: {0,2,4}:2
 
GPU  0 Profile ID  9 Placements: {0,4}:4
GPU  0 Profile ID  5 Placement : {0}:4
GPU  0 Profile ID  0 Placement : {0}:8
</syntaxhighlight> 
== Creating GPU Instances ==
== Creating GPU Instances ==
Without creating GPU instances (and corresponding compute instances), CUDA workloads cannot be run on the GPU.  
Without creating GPU instances (and corresponding compute instances), CUDA workloads cannot be run on the GPU.  


Creating GPU instances using the <samp>-cgi</samp> option. One of three options can be used to specify the instance profiles to be created:
Creating GPU instances using the <samp>-cgi</samp> and create the corresponding Compute Instances (CI). By using the <samp>-C</samp> option


# Profile ID (e.g. 9, 14, 5)
<nowiki>**</nowiki> Running CUDA workloads on the GPU requires the creation of MIG partitions along with their corresponding compute instances <syntaxhighlight lang="bash">
# Short name of the profile (e.g. <samp>3g.20gb</samp>
# no GPU instances yet
# Full profile name of the instance (e.g. <samp>MIG 3g.20gb</samp>)                               
$ nvidia-smi mig -lgi
No GPU instances found: Not Found


Once the GPU instances are created, one needs to create the corresponding Compute Instances (CI). By using the                            <samp>-C</samp> option  
# Create 9,19,19,19 partitions
# -cgi : this flag specifies the MIG partition configuration. The numbers following the flag represent the MIG partitions for each of the four MIG device slices. In this case, there are four slices with configurations 9, 19, 19, and 19 compute instances each. These numbers correspond to the profile IDs retrieved previously
# creates the corresponding compute instances for the MIG partitions automatically
$ sudo nvidia-smi mig -cgi 9,19,19,19 -C
Successfully created GPU instance ID  2 on GPU  0 using profile MIG 3g.47gb (ID  9)
Successfully created compute instance ID  0 on GPU  0 GPU instance ID  2 using profile MIG 3g.47gb (ID  2)
Successfully created GPU instance ID  7 on GPU  0 using profile MIG 1g.12gb (ID 19)
Successfully created compute instance ID  0 on GPU  0 GPU instance ID  7 using profile MIG 1g.12gb (ID  0)
Successfully created GPU instance ID  8 on GPU  0 using profile MIG 1g.12gb (ID 19)
Successfully created compute instance ID  0 on GPU  0 GPU instance ID  8 using profile MIG 1g.12gb (ID  0)
Successfully created GPU instance ID  9 on GPU  0 using profile MIG 1g.12gb (ID 19)
Successfully created compute instance ID  0 on GPU  0 GPU instance ID  9 using profile MIG 1g.12gb (ID 0)


Example, create two GPU instances (of type <samp>3g.20gb</samp>), with each GPU instance having half of the available compute and memory capacityv
# List current MIG GPU instances
<kbd>$ sudo nvidia-smi mig -cgi 9,3g.20gb -C</kbd>
$ sudo nvidia-smi mig -lgi
Successfully created GPU instance ID  2 on GPU  0 using profile MIG 3g.20gb (ID  9)
+-------------------------------------------------------+
Successfully created compute instance ID  0 on GPU 0 GPU instance ID 2 using profile MIG 3g.20gb (ID 2)
| GPU instances:                                        |
Successfully created GPU instance ID 1 on GPU  0 using profile MIG 3g.20gb (ID  9)
| GPU   Name            Profile Instance  Placement |
Successfully created compute instance ID  0 on GPU  0 GPU instance ID  1 using profile MIG 3g.20gb (ID  2)
|                          ID      ID       Start:Size |
|=======================================================|
|  0 MIG 1g.12gb        19        7          0:1    |
  $ sudo nvidia-smi mig -lgi
+-------------------------------------------------------+
+----------------------------------------------------+
|  0 MIG 1g.12gb        19        8          1:1    |
  | GPU instances:                                     |
+-------------------------------------------------------+
| GPU  Name          Profile  Instance  Placement  |
|  0  MIG 1g.12gb        19        9          2:1     |
|                      ID      ID      Start:Size |
+-------------------------------------------------------+
|====================================================|
|  0  MIG 3g.47gb          9        2          4:4    |
|  0  MIG 3g.20gb      9       1         4:4     |
+-------------------------------------------------------+
+----------------------------------------------------+
</syntaxhighlight>List up MIG devices<syntaxhighlight lang="bash">
|  0  MIG 3g.20gb      9        2          0:4    |
# Show GPU UUID, docker container can use the UUID
+----------------------------------------------------+
$ nvidia-smi -L
GPU 0: NVIDIA H100 NVL (UUID: GPU-d2481ba7-bc0a-5ff0-0d5b-b4ba1d4d56c5)
#Now verify that the GIs and corresponding CIs are created:
  MIG 3g.47gb    Device  0: (UUID: MIG-45174f60-85a9-51f4-bc61-f6dc57dc60e1)
  MIG 1g.12gb    Device  1: (UUID: MIG-b6bbb81c-71b7-54a2-a621-9b2a12215cab)
$ nvidia-smi
  MIG 1g.12gb    Device  2: (UUID: MIG-ea284e9f-1cfb-5980-8948-bc86b7c1ae71)
+-----------------------------------------------------------------------------+
  MIG 1g.12gb    Device  3: (UUID: MIG-2bbae2fb-2ef8-5917-badf-b0571b1381cf)
| MIG devices:                                                                |
 
+------------------+----------------------+-----------+-----------------------+
# Show physical GPU and MIG devices
| GPU  GI  CI  MIG |        Memory-Usage |        Vol|        Shared        |
$ nvidia-smi
|      ID  ID  Dev |                      | SM    Unc| CE  ENC  DEC  OFA  JPG|
Sun May 25 22:19:13 2025     
  |                 |                     |       ECC|                       |
+-----------------------------------------------------------------------------------------+
|==================+======================+===========+=======================|
| NVIDIA-SMI 570.124.04            Driver Version: 570.124.04    CUDA Version: 12.8    |
  | 0    1   0  0 |    11MiB / 20224MiB | 42     0 | 3  0    2    0    0 |
|-----------------------------------------+------------------------+----------------------+
+------------------+----------------------+-----------+-----------------------+
| GPU Name                Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
|  0    2  0  1  |    11MiB / 20096MiB | 42      0 |  3  0    2    0    0 |
| Fan  Temp  Perf          Pwr:Usage/Cap |          Memory-Usage | GPU-Util  Compute M. |
+------------------+----------------------+-----------+-----------------------+
|                                        |                        |               MIG M. |
                                                                               
|=========================================+========================+======================|
+-----------------------------------------------------------------------------+
|  0  NVIDIA H100 NVL                On |  00000000:4F:00.0 Off |                  On |
  | Processes:                                                                  |
| N/A   38C    P0            58W /  400W |      87MiB / 95830MiB |    N/A     Default |
  | GPU  GI  CI        PID  Type  Process name                  GPU Memory |
|                                        |                        |              Enabled |
|        ID  ID                                                  Usage      |
+-----------------------------------------+------------------------+----------------------+
|=============================================================================|
 
|  No running processes found                                                 |
+-----------------------------------------------------------------------------------------+
+-----------------------------------------------------------------------------+
| MIG devices:                                                                            |
+------------------+----------------------------------+-----------+-----------------------+
| GPU GI  CI MIG |                     Memory-Usage |       Vol|        Shared        |
|     ID  ID  Dev |                      BAR1-Usage | SM    Unc| CE ENC  DEC  OFA  JPG |
|                  |                                  |        ECC|                      |
|==================+==================================+===========+=======================|
|  0    2  0  0  |              44MiB / 47488MiB    | 60      0 |  3  0    3    0    3 |
|                  |                0MiB / 65535MiB  |          |                      |
+------------------+----------------------------------+-----------+-----------------------+
|  0    7  0  1  |              15MiB / 11008MiB    | 16      0 |  1  0    1    0    1 |
|                  |                0MiB / 16383MiB  |          |                      |
+------------------+----------------------------------+-----------+-----------------------+
|  0    8  0  2  |              15MiB / 11008MiB    | 16      0 |  1  0    1    0    1 |
|                  |                0MiB / 16383MiB  |          |                      |
+------------------+----------------------------------+-----------+-----------------------+
|  0    9  0  3  |              15MiB / 11008MiB    | 16      0 |  1  0    1    0    1 |
|                  |                0MiB / 16383MiB  |          |                      |
+------------------+----------------------------------+-----------+-----------------------+
| Processes:                                                                              |
|  GPU  GI  CI              PID  Type  Process name                        GPU Memory |
|        ID  ID                                                              Usage      |
|=========================================================================================|
|  No running processes found                                                            |
+-----------------------------------------------------------------------------------------+
</syntaxhighlight>
 
== Use MIG device ==
<syntaxhighlight lang="bash">
# To use specific GPU instance, need to check device ID or MIG UUID
$ nvidia-smi -L
GPU 0: NVIDIA H100 NVL (UUID: GPU-d2481ba7-bc0a-5ff0-0d5b-b4ba1d4d56c5)
  MIG 3g.47gb    Device  0: (UUID: MIG-45174f60-85a9-51f4-bc61-f6dc57dc60e1)
  MIG 1g.12gb    Device  1: (UUID: MIG-b6bbb81c-71b7-54a2-a621-9b2a12215cab)
  MIG 1g.12gb    Device  2: (UUID: MIG-ea284e9f-1cfb-5980-8948-bc86b7c1ae71)
  MIG 1g.12gb    Device  3: (UUID: MIG-2bbae2fb-2ef8-5917-badf-b0571b1381cf)
 
# Use Device id 2 on docker container
$ docker run --gpus '"device=MIG-ea284e9f-1cfb-5980-8948-bc86b7c1ae71"' --rm nvidia/cuda:11.8.0-base-ubuntu20.04 nvidia-smi 
Sun May 25 22:56:04 2025     
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 570.124.04            Driver Version: 570.124.04    CUDA Version: 12.8    |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf          Pwr:Usage/Cap |          Memory-Usage | GPU-Util  Compute M. |
|                                        |                        |              MIG M. |
|=========================================+========================+======================|
|  0  NVIDIA H100 NVL                On  |  00000000:4F:00.0 Off |                  On |
| N/A  39C    P0            59W /  400W |                  N/A  |    N/A      Default |
|                                        |                        |              Enabled |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| MIG devices:                                                                            |
+------------------+----------------------------------+-----------+-----------------------+
| GPU  GI  CI  MIG |                    Memory-Usage |        Vol|        Shared        |
|      ID  ID  Dev |                      BAR1-Usage | SM    Unc| CE ENC  DEC  OFA  JPG |
|                  |                                  |        ECC|                      |
|==================+==================================+===========+=======================|
|  0    8  0  0  |              15MiB / 11008MiB    | 16      0 |  1  0    1    0    1 |
|                  |                0MiB / 16383MiB  |          |                      |
+------------------+----------------------------------+-----------+-----------------------+
| Processes:                                                                              |
|  GPU  GI  CI              PID  Type  Process name                        GPU Memory |
|        ID  ID                                                              Usage      |
|=========================================================================================|
|  No running processes found                                                            |
+-----------------------------------------------------------------------------------------+
 
# In short, we can also use GPUID:MIG's DeviceID instead of UUID
$ docker run --gpus '"device=0:1"' --rm nvidia/cuda:11.8.0-base-ubuntu20.04 nvidia-smi
Sun May 25 22:56:47 2025     
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 570.124.04            Driver Version: 570.124.04    CUDA Version: 12.8    |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf          Pwr:Usage/Cap |          Memory-Usage | GPU-Util  Compute M. |
|                                        |                        |              MIG M. |
|=========================================+========================+======================|
|  0  NVIDIA H100 NVL                On  |  00000000:4F:00.0 Off |                  On |
| N/A  39C    P0            59W /  400W |                  N/A  |    N/A      Default |
|                                        |                        |              Enabled |
+-----------------------------------------+------------------------+----------------------+
 
+-----------------------------------------------------------------------------------------+
| MIG devices:                                                                            |
+------------------+----------------------------------+-----------+-----------------------+
| GPU  GI  CI  MIG |                    Memory-Usage |        Vol|        Shared        |
|      ID  ID  Dev |                      BAR1-Usage | SM    Unc| CE ENC  DEC  OFA  JPG |
|                  |                                  |        ECC|                      |
|==================+==================================+===========+=======================|
|  0    7  0  0  |              15MiB / 11008MiB    | 16      0 |  1  0    1    0    1 |
|                  |                0MiB / 16383MiB  |          |                      |
+------------------+----------------------------------+-----------+-----------------------+
 
| Processes:                                                                              |
|  GPU  GI  CI              PID  Type  Process name                        GPU Memory |
|        ID  ID                                                              Usage      |
|=========================================================================================|
|  No running processes found                                                             |
+-----------------------------------------------------------------------------------------+
</syntaxhighlight>


== Destroying GPU Instances ==
== Destroying GPU Instances ==
<kbd>destroy all the CIs and GIs</kbd>
 
<kbd>$ sudo nvidia-smi mig -dci && sudo nvidia-smi mig -dgi</kbd>
=== <kbd>destroy all the CIs and GIs</kbd> ===
  Successfully destroyed compute instance ID  0 from GPU  0 GPU instance ID  1
<syntaxhighlight lang="bash">
Successfully destroyed compute instance ID  1 from GPU  0 GPU instance ID  1
$ sudo nvidia-smi mig -dci && sudo nvidia-smi mig -dgi
Successfully destroyed compute instance ID  2 from GPU  0 GPU instance ID  1
Successfully destroyed compute instance ID  0 from GPU  0 GPU instance ID 7
  Successfully destroyed GPU instance ID  1 from GPU  0
Successfully destroyed compute instance ID  0 from GPU  0 GPU instance ID  8
  Successfully destroyed GPU instance ID  2 from GPU  0  
Successfully destroyed compute instance ID  0 from GPU  0 GPU instance ID  9
delete the specific CIs created under GI 1
Successfully destroyed compute instance ID  0 from GPU  0 GPU instance ID  2
Successfully destroyed GPU instance ID 7 from GPU  0
Successfully destroyed GPU instance ID  8 from GPU  0
Successfully destroyed GPU instance ID  9 from GPU 0
Successfully destroyed GPU instance ID  2 from GPU  0
</syntaxhighlight>
 
=== delete the specific CIs created under GI 1 ===
  <kbd>$ sudo nvidia-smi mig -dci -ci 0,1,2 -gi 1</kbd>
  <kbd>$ sudo nvidia-smi mig -dci -ci 0,1,2 -gi 1</kbd>
  Successfully destroyed compute instance ID  0 from GPU  0 GPU instance ID  1
  Successfully destroyed compute instance ID  0 from GPU  0 GPU instance ID  1
  Successfully destroyed compute instance ID  1 from GPU  0 GPU instance ID  1
  Successfully destroyed compute instance ID  1 from GPU  0 GPU instance ID  1
  Successfully destroyed compute instance ID  2 from GPU  0 GPU instance ID  1
  Successfully destroyed compute instance ID  2 from GPU  0 GPU instance ID  1
       


== <kbd>Monitoring MIG Devices</kbd> ==  
== <kbd>Monitoring MIG Devices</kbd> ==


== MIG limitation ==
== MIG limitation ==
Line 200: Line 322:
| colspan="1" rowspan="1" |7
| colspan="1" rowspan="1" |7
|-
|-
| colspan="1" rowspan="1" |H100-[[PCIe|PCIE]]
| colspan="1" rowspan="1" |H100-[[PCIe|PCIE]] (Inc, NVL)
| colspan="1" rowspan="1" |Hopper
| colspan="1" rowspan="1" |Hopper
| colspan="1" rowspan="1" |GH100
| colspan="1" rowspan="1" |GH100
| colspan="1" rowspan="1" |9.0
| colspan="1" rowspan="1" |9.0
| colspan="1" rowspan="1" |80GB
| colspan="1" rowspan="1" |80GB (94GB)
| colspan="1" rowspan="1" |7
| colspan="1" rowspan="1" |7
|-
|-

Revision as of 08:03, 26 May 2025

NVIDIA Multi-Instance GPU

NVIDIA introduced MIG(Multi-Instance GPU) since Ampere architecture in 2020.


If we use a single GPU to run more than one application, those applications compete on using GPU resources which is known as resource contention. However, with MIG, an GPU instance is completely put aside for a specific application. MIG feature allows a single GPU into multiple fully isolated virtual GPU devices that are efficiently sized per-user-case, specifically smaller use-cases that only require a subset of GPU resources.


MIG ensures to providing each instance's processors have separate and isolated paths through the entire memory system - the on-chip crossbar ports, L2 cache banks, memory controllers, and DRAM address busses are all assigned uniquely to an individual instanceenhanced isolation GPU resources.

nvidia-mig-example

Benefits of MIG on MIG featured GPU are

  • Physical allocation of resourdces used by parallel GPU workloads - Secure multi-tenant environments with isolation and predictable QoS
  • Versatile profiles with dynamic configuration - Maximized utilization by configuring for specfic workloads
  • CUDA programming model unchanged

MIG Teminology

MIG feature allows one or more GPU instances to be allocated within a GPU. so that a single GPU appear as if it were many.

GPU instalace(GI)

is a fully isolated collection of all physical GPU resources such as GPU memory, GPU SMs. it can contain one or more GPU compute instances

Compute instance(CI)

is an isolated collection of GPU SMs (CUDA cores) belongs to a single GPU instance. so that it provides partial isolation within the GPU instance for compute resourdces and independent workload scheduling.

MIG device

is made up with GPU instance and a compute instance. MIG devices are assigned GPU UUIDs and can be displayed with 

$nvidia-smi -L

To use MIG feature effectivly, clock speed, MIG profile congifuration, and other settings should be optimized base on the expected MIG use-case. There is no 'best' or 'optimal' combination of profiles and configurations. however, this table shows NVIDIA recommended workload types for the different MIG sizes of the A100

GPU Slice

is the smallest fraction of the GPU that combines a single GPU memory slice and a single GPU SM slice

GPU Memory Slice

is the smallest fraction of the GPU's memory including the corresponding memory controllers and cache. generally it is roughly 1/8 of the total GPU memory resources.

GPU SM Slice

the smallest fraction of the GPU's SMs. generally it is roughly 1/7 of the total number of SMs

GPU Engine

what executes job on the GPU that scheduled independently and work in a GPU context. different engines are responsible for different actions such as compute engine or copy engine

MIG Configuration (profile)

GPU reset required to enable or disable MIG mode, this is one-time operation per GPU and persists across system reboots.


The number of slices that a GI can be created with is not arbitrary. The NVIDIA driver APIs provide a number of “GPU Instance Profiles” and users can create GIs by specifying one of these profiles.  18 combinations possible. 

# H100 NVL, show available MIG profiles
$ nvidia-smi mig -lgip
+-----------------------------------------------------------------------------+
| GPU instance profiles:                                                      |
| GPU   Name             ID    Instances   Memory     P2P    SM    DEC   ENC  |
|                              Free/Total   GiB              CE    JPEG  OFA  |
|=============================================================================|
|   0  MIG 1g.12gb       19     7/7        10.75      No     16     1     0   |
|                                                             1     1     0   |
+-----------------------------------------------------------------------------+
|   0  MIG 1g.12gb+me    20     1/1        10.75      No     16     1     0   |
|                                                             1     1     1   |
+-----------------------------------------------------------------------------+
|   0  MIG 1g.24gb       15     4/4        21.62      No     26     1     0   |
|                                                             1     1     0   |
+-----------------------------------------------------------------------------+
|   0  MIG 2g.24gb       14     3/3        21.62      No     32     2     0   |
|                                                             2     2     0   |
+-----------------------------------------------------------------------------+
|   0  MIG 3g.47gb        9     2/2        46.38      No     60     3     0   |
|                                                             3     3     0   |
+-----------------------------------------------------------------------------+
|   0  MIG 4g.47gb        5     1/1        46.38      No     64     4     0   |
|                                                             4     4     0   |
+-----------------------------------------------------------------------------+
|   0  MIG 7g.94gb        0     1/1        93.12      No     132    7     0   |
|                                                             8     7     1   |
+-----------------------------------------------------------------------------+

Enable MIG Mode

When MIG is enabled on the GPU, depending on the GPU product, the driver will attempt to reset the GPU so that MIG mode can take effect.                                        

$ sudo nvidia-smi -pm 1     # persistence mode is required to enable MIG
Enabled Legacy persistence mode for GPU 00000000:4F:00.0.
All done.

$ sudo nvidia-smi -mig 1    # Enable MIG 
Enabled MIG Mode for GPU 00000000:4F:00.0
All done.

#Verify enabled MIG mode 
$ nvidia-smi --query-gpu=pci.bus_id,mig.mode.current --format=csv             
pci.bus_id, mig.mode.current
00000000:4F:00.0, Enabled

If encounter a message saying “Warning: MIG mode is in pending enable state for GPU XXX:XX:XX.X:In use by another client …”, when enabling MIG. you need to stop nvsm and dcgm, then try again.[1] 

$ sudo systemctl stop nvsm
$ sudo systemctl stop dcgm
$ sudo nvidia-smi -i 0 -mig 1

** Reference MIG user guide for various post processing of MIG configuration change to take effect.

List GPU Instance Profiles

List the possible placements available using the following command. it would be helpful to review performance of different MIG instance size using MLPerf with Single Shot MultiBox Detector (SSD) training benchmark.

The syntax of the placement is {<index>}:<GPU Slice Count> and shows the placement of the instances on the GPU 

#H100 NVL, list possible placements 
#The syntax of the placement output is {<index>}:<GPU Slice Count> and shows the placement of the instances on the GPU
$ nvidia-smi mig -lgipp
GPU  0 Profile ID 19 Placements: {0,1,2,3,4,5,6}:1
GPU  0 Profile ID 20 Placements: {0,1,2,3,4,5,6}:1
GPU  0 Profile ID 15 Placements: {0,2,4,6}:2
GPU  0 Profile ID 14 Placements: {0,2,4}:2
GPU  0 Profile ID  9 Placements: {0,4}:4
GPU  0 Profile ID  5 Placement : {0}:4
GPU  0 Profile ID  0 Placement : {0}:8

Creating GPU Instances

Without creating GPU instances (and corresponding compute instances), CUDA workloads cannot be run on the GPU.

Creating GPU instances using the -cgi and create the corresponding Compute Instances (CI). By using the -C option

** Running CUDA workloads on the GPU requires the creation of MIG partitions along with their corresponding compute instances 

# no GPU instances yet 
$ nvidia-smi mig -lgi
No GPU instances found: Not Found

# Create 9,19,19,19 partitions 
# -cgi : this flag specifies the MIG partition configuration. The numbers following the flag represent the MIG partitions for each of the four MIG device slices. In this case, there are four slices with configurations 9, 19, 19, and 19 compute instances each. These numbers correspond to the profile IDs retrieved previously
# creates the corresponding compute instances for the MIG partitions automatically
$ sudo nvidia-smi mig -cgi 9,19,19,19 -C
Successfully created GPU instance ID  2 on GPU  0 using profile MIG 3g.47gb (ID  9)
Successfully created compute instance ID  0 on GPU  0 GPU instance ID  2 using profile MIG 3g.47gb (ID  2)
Successfully created GPU instance ID  7 on GPU  0 using profile MIG 1g.12gb (ID 19)
Successfully created compute instance ID  0 on GPU  0 GPU instance ID  7 using profile MIG 1g.12gb (ID  0)
Successfully created GPU instance ID  8 on GPU  0 using profile MIG 1g.12gb (ID 19)
Successfully created compute instance ID  0 on GPU  0 GPU instance ID  8 using profile MIG 1g.12gb (ID  0)
Successfully created GPU instance ID  9 on GPU  0 using profile MIG 1g.12gb (ID 19)
Successfully created compute instance ID  0 on GPU  0 GPU instance ID  9 using profile MIG 1g.12gb (ID  0)

# List current MIG GPU instances
$ sudo nvidia-smi mig -lgi
+-------------------------------------------------------+
| GPU instances:                                        |
| GPU   Name             Profile  Instance   Placement  |
|                          ID       ID       Start:Size |
|=======================================================|
|   0  MIG 1g.12gb         19        7          0:1     |
+-------------------------------------------------------+
|   0  MIG 1g.12gb         19        8          1:1     |
+-------------------------------------------------------+
|   0  MIG 1g.12gb         19        9          2:1     |
+-------------------------------------------------------+
|   0  MIG 3g.47gb          9        2          4:4     |
+-------------------------------------------------------+

List up MIG devices

# Show GPU UUID, docker container can use the UUID
$ nvidia-smi -L
GPU 0: NVIDIA H100 NVL (UUID: GPU-d2481ba7-bc0a-5ff0-0d5b-b4ba1d4d56c5)
  MIG 3g.47gb     Device  0: (UUID: MIG-45174f60-85a9-51f4-bc61-f6dc57dc60e1)
  MIG 1g.12gb     Device  1: (UUID: MIG-b6bbb81c-71b7-54a2-a621-9b2a12215cab)
  MIG 1g.12gb     Device  2: (UUID: MIG-ea284e9f-1cfb-5980-8948-bc86b7c1ae71)
  MIG 1g.12gb     Device  3: (UUID: MIG-2bbae2fb-2ef8-5917-badf-b0571b1381cf)

# Show physical GPU and MIG devices 
$ nvidia-smi 
Sun May 25 22:19:13 2025       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 570.124.04             Driver Version: 570.124.04     CUDA Version: 12.8     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA H100 NVL                On  |   00000000:4F:00.0 Off |                   On |
| N/A   38C    P0             58W /  400W |      87MiB /  95830MiB |     N/A      Default |
|                                         |                        |              Enabled |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| MIG devices:                                                                            |
+------------------+----------------------------------+-----------+-----------------------+
| GPU  GI  CI  MIG |                     Memory-Usage |        Vol|        Shared         |
|      ID  ID  Dev |                       BAR1-Usage | SM     Unc| CE ENC  DEC  OFA  JPG |
|                  |                                  |        ECC|                       |
|==================+==================================+===========+=======================|
|  0    2   0   0  |              44MiB / 47488MiB    | 60      0 |  3   0    3    0    3 |
|                  |                 0MiB / 65535MiB  |           |                       |
+------------------+----------------------------------+-----------+-----------------------+
|  0    7   0   1  |              15MiB / 11008MiB    | 16      0 |  1   0    1    0    1 |
|                  |                 0MiB / 16383MiB  |           |                       |
+------------------+----------------------------------+-----------+-----------------------+
|  0    8   0   2  |              15MiB / 11008MiB    | 16      0 |  1   0    1    0    1 |
|                  |                 0MiB / 16383MiB  |           |                       |
+------------------+----------------------------------+-----------+-----------------------+
|  0    9   0   3  |              15MiB / 11008MiB    | 16      0 |  1   0    1    0    1 |
|                  |                 0MiB / 16383MiB  |           |                       |
+------------------+----------------------------------+-----------+-----------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|  No running processes found                                                             |
+-----------------------------------------------------------------------------------------+

Use MIG device

# To use specific GPU instance, need to check device ID or MIG UUID
$ nvidia-smi -L
GPU 0: NVIDIA H100 NVL (UUID: GPU-d2481ba7-bc0a-5ff0-0d5b-b4ba1d4d56c5)
  MIG 3g.47gb     Device  0: (UUID: MIG-45174f60-85a9-51f4-bc61-f6dc57dc60e1)
  MIG 1g.12gb     Device  1: (UUID: MIG-b6bbb81c-71b7-54a2-a621-9b2a12215cab)
  MIG 1g.12gb     Device  2: (UUID: MIG-ea284e9f-1cfb-5980-8948-bc86b7c1ae71)
  MIG 1g.12gb     Device  3: (UUID: MIG-2bbae2fb-2ef8-5917-badf-b0571b1381cf)

# Use Device id 2 on docker container 
$ docker run --gpus '"device=MIG-ea284e9f-1cfb-5980-8948-bc86b7c1ae71"' --rm nvidia/cuda:11.8.0-base-ubuntu20.04 nvidia-smi   
Sun May 25 22:56:04 2025       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 570.124.04             Driver Version: 570.124.04     CUDA Version: 12.8     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA H100 NVL                On  |   00000000:4F:00.0 Off |                   On |
| N/A   39C    P0             59W /  400W |                  N/A   |     N/A      Default |
|                                         |                        |              Enabled |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| MIG devices:                                                                            |
+------------------+----------------------------------+-----------+-----------------------+
| GPU  GI  CI  MIG |                     Memory-Usage |        Vol|        Shared         |
|      ID  ID  Dev |                       BAR1-Usage | SM     Unc| CE ENC  DEC  OFA  JPG |
|                  |                                  |        ECC|                       |
|==================+==================================+===========+=======================|
|  0    8   0   0  |              15MiB / 11008MiB    | 16      0 |  1   0    1    0    1 |
|                  |                 0MiB / 16383MiB  |           |                       |
+------------------+----------------------------------+-----------+-----------------------+
| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|  No running processes found                                                             |
+-----------------------------------------------------------------------------------------+

# In short, we can also use GPUID:MIG's DeviceID instead of UUID
$ docker run --gpus '"device=0:1"' --rm nvidia/cuda:11.8.0-base-ubuntu20.04 nvidia-smi 
Sun May 25 22:56:47 2025       
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 570.124.04             Driver Version: 570.124.04     CUDA Version: 12.8     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA H100 NVL                On  |   00000000:4F:00.0 Off |                   On |
| N/A   39C    P0             59W /  400W |                  N/A   |     N/A      Default |
|                                         |                        |              Enabled |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| MIG devices:                                                                            |
+------------------+----------------------------------+-----------+-----------------------+
| GPU  GI  CI  MIG |                     Memory-Usage |        Vol|        Shared         |
|      ID  ID  Dev |                       BAR1-Usage | SM     Unc| CE ENC  DEC  OFA  JPG |
|                  |                                  |        ECC|                       |
|==================+==================================+===========+=======================|
|  0    7   0   0  |              15MiB / 11008MiB    | 16      0 |  1   0    1    0    1 |
|                  |                 0MiB / 16383MiB  |           |                       |
+------------------+----------------------------------+-----------+-----------------------+

| Processes:                                                                              |
|  GPU   GI   CI              PID   Type   Process name                        GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|  No running processes found                                                             |
+-----------------------------------------------------------------------------------------+

Destroying GPU Instances

destroy all the CIs and GIs

$ sudo nvidia-smi mig -dci && sudo nvidia-smi mig -dgi
Successfully destroyed compute instance ID  0 from GPU  0 GPU instance ID  7
Successfully destroyed compute instance ID  0 from GPU  0 GPU instance ID  8
Successfully destroyed compute instance ID  0 from GPU  0 GPU instance ID  9
Successfully destroyed compute instance ID  0 from GPU  0 GPU instance ID  2
Successfully destroyed GPU instance ID  7 from GPU  0
Successfully destroyed GPU instance ID  8 from GPU  0
Successfully destroyed GPU instance ID  9 from GPU  0
Successfully destroyed GPU instance ID  2 from GPU  0

delete the specific CIs created under GI 1

$ sudo nvidia-smi mig -dci -ci 0,1,2 -gi 1
Successfully destroyed compute instance ID  0 from GPU  0 GPU instance ID  1
Successfully destroyed compute instance ID  1 from GPU  0 GPU instance ID  1
Successfully destroyed compute instance ID  2 from GPU  0 GPU instance ID  1

Monitoring MIG Devices

MIG limitation

  • Graphics contexts not supported
  • P2P not available (no NVLink)

MIG supported GPUs[2]

Product Architecture Microarchitecture Compute Capability Memory Size Max Number of Instances
H100-SXM5 Hopper GH100 9.0 80GB 7
H100-PCIE (Inc, NVL) Hopper GH100 9.0 80GB (94GB) 7
A100-SXM4 NVIDIA Ampere GA100 8.0 40GB 7
A100-SXM4 NVIDIA Ampere GA100 8.0 80GB 7
A100-PCIE NVIDIA Ampere GA100 8.0 40GB 7
A100-PCIE NVIDIA Ampere GA100 8.0 80GB 7
A30 NVIDIA Ampere GA100 8.0 24GB 4

References

  1. ↑ https://docs.nvidia.com/datacenter/tesla/mig-user-guide/
  2. ↑ https://docs.nvidia.com/datacenter/tesla/mig-user-guide/
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