CryoSPARC Guide
  • About CryoSPARC
  • Current Version
  • Licensing
    • Non-commercial license agreement
  • Setup, Configuration and Management
    • CryoSPARC Architecture and System Requirements
    • CryoSPARC Installation Prerequisites
    • How to Download, Install and Configure
      • Obtaining A License ID
      • Downloading and Installing CryoSPARC
      • CryoSPARC Cluster Integration Script Examples
      • Accessing the CryoSPARC User Interface
    • Deploying CryoSPARC on AWS
      • Performance Benchmarks
    • Using CryoSPARC with Cluster Management Software
    • Software Updates and Patches
    • Management and Monitoring
      • Environment variables
      • (Optional) Hosting CryoSPARC Through a Reverse Proxy
      • cryosparcm reference
      • cryosparcm cli reference
      • cryosparcw reference
    • Software System Guides
      • Guide: Updating to CryoSPARC v4
      • Guide: Installation Testing with cryosparcm test
      • Guide: Verify CryoSPARC Installation with the Extensive Validation Job (v4.3+)
      • Guide: Verify CryoSPARC Installation with the Extensive Workflow (≤v4.2)
      • Guide: Performance Benchmarking (v4.3+)
      • Guide: Download Error Reports
      • Guide: Maintenance Mode and Configurable User Facing Messages
      • Guide: User Management
      • Guide: Multi-user Unix Permissions and Data Access Control
      • Guide: Lane Assignments and Restrictions
      • Guide: Queuing Directly to a GPU
      • Guide: Priority Job Queuing
      • Guide: Configuring Custom Variables for Cluster Job Submission Scripts
      • Guide: SSD Particle Caching in CryoSPARC
      • Guide: Data Management in CryoSPARC (v4.0+)
      • Guide: Data Cleanup (v4.3+)
      • Guide: Reduce Database Size (v4.3+)
      • Guide: Data Management in CryoSPARC (≤v3.3)
      • Guide: CryoSPARC Live Session Data Management
      • Guide: Manipulating .cs Files Created By CryoSPARC
      • Guide: Migrating your CryoSPARC Instance
      • Guide: EMDB-friendly XML file for FSC plots
    • Troubleshooting
  • Application Guide (v4.0+)
    • A Tour of the CryoSPARC Interface
    • Browsing the CryoSPARC Instance
    • Projects, Workspaces and Live Sessions
    • Jobs
    • Job Views: Cards, Tree, and Table
    • Creating and Running Jobs
    • Low Level Results Interface
    • Filters and Sorting
    • View Options
    • Tags
    • Flat vs Hierarchical Navigation
    • File Browser
    • Blueprints
    • Workflows
    • Inspecting Data
    • Managing Jobs
    • Interactive Jobs
    • Upload Local Files
    • Managing Data
    • Downloading and Exporting Data
    • Instance Management
    • Admin Panel
  • Cryo-EM Foundations
    • Image Formation
      • Contrast in Cryo-EM
      • Waves as Vectors
      • Aliasing
  • Expectation Maximization in Cryo-EM
  • Processing Data in cryoSPARC
    • Get Started with CryoSPARC: Introductory Tutorial (v4.0+)
    • Tutorial Videos
    • All Job Types in CryoSPARC
      • Import
        • Job: Import Movies
        • Job: Import Micrographs
        • Job: Import Particle Stack
        • Job: Import 3D Volumes
        • Job: Import Templates
        • Job: Import Result Group
        • Job: Import Beam Shift
      • Motion Correction
        • Job: Patch Motion Correction
        • Job: Full-Frame Motion Correction
        • Job: Local Motion Correction
        • Job: MotionCor2 (Wrapper) (BETA)
        • Job: Reference Based Motion Correction (BETA)
      • CTF Estimation
        • Job: Patch CTF Estimation
        • Job: Patch CTF Extraction
        • Job: CTFFIND4 (Wrapper)
        • Job: Gctf (Wrapper) (Legacy)
      • Exposure Curation
        • Job: Micrograph Denoiser (BETA)
        • Job: Micrograph Junk Detector (BETA)
        • Interactive Job: Manually Curate Exposures
      • Particle Picking
        • Interactive Job: Manual Picker
        • Job: Blob Picker
        • Job: Template Picker
        • Job: Filament Tracer
        • Job: Blob Picker Tuner
        • Interactive Job: Inspect Particle Picks
        • Job: Create Templates
      • Extraction
        • Job: Extract from Micrographs
        • Job: Downsample Particles
        • Job: Restack Particles
      • Deep Picking
        • Guideline for Supervised Particle Picking using Deep Learning Models
        • Deep Network Particle Picker
          • T20S Proteasome: Deep Particle Picking Tutorial
          • Job: Deep Picker Train and Job: Deep Picker Inference
        • Topaz (Bepler, et al)
          • T20S Proteasome: Topaz Particle Picking Tutorial
          • T20S Proteasome: Topaz Micrograph Denoising Tutorial
          • Job: Topaz Train and Job: Topaz Cross Validation
          • Job: Topaz Extract
          • Job: Topaz Denoise
      • Particle Curation
        • Job: 2D Classification
        • Interactive Job: Select 2D Classes
        • Job: Reference Based Auto Select 2D (BETA)
        • Job: Reconstruct 2D Classes
        • Job: Rebalance 2D Classes
        • Job: Class Probability Filter (Legacy)
        • Job: Rebalance Orientations
        • Job: Subset Particles by Statistic
      • 3D Reconstruction
        • Job: Ab-Initio Reconstruction
      • 3D Refinement
        • Job: Homogeneous Refinement
        • Job: Heterogeneous Refinement
        • Job: Non-Uniform Refinement
        • Job: Homogeneous Reconstruction Only
        • Job: Heterogeneous Reconstruction Only
        • Job: Homogeneous Refinement (Legacy)
        • Job: Non-uniform Refinement (Legacy)
      • CTF Refinement
        • Job: Global CTF Refinement
        • Job: Local CTF Refinement
        • Job: Exposure Group Utilities
      • Conformational Variability
        • Job: 3D Variability
        • Job: 3D Variability Display
        • Job: 3D Classification
        • Job: Regroup 3D Classes
        • Job: Reference Based Auto Select 3D (BETA)
        • Job: 3D Flexible Refinement (3DFlex) (BETA)
      • Postprocessing
        • Job: Sharpening Tools
        • Job: DeepEMhancer (Wrapper)
        • Job: Validation (FSC)
        • Job: Local Resolution Estimation
        • Job: Local Filtering
        • Job: ResLog Analysis
        • Job: ThreeDFSC (Wrapper) (Legacy)
      • Local Refinement
        • Job: Local Refinement
        • Job: Particle Subtraction
        • Job: Local Refinement (Legacy)
      • Helical Reconstruction
        • Helical symmetry in CryoSPARC
        • Job: Helical Refinement
        • Job: Symmetry search utility
        • Job: Average Power Spectra
      • Utilities
        • Job: Exposure Sets Tool
        • Job: Exposure Tools
        • Job: Generate Micrograph Thumbnails
        • Job: Cache Particles on SSD
        • Job: Check for Corrupt Particles
        • Job: Particle Sets Tool
        • Job: Reassign Particles to Micrographs
        • Job: Remove Duplicate Particles
        • Job: Symmetry Expansion
        • Job: Volume Tools
        • Job: Volume Alignment Tools
        • Job: Align 3D maps
        • Job: Split Volumes Group
        • Job: Orientation Diagnostics
      • Simulations
        • Job: Simulate Data (GPU)
        • Job: Simulate Data (Legacy)
    • CryoSPARC Tools
    • Data Processing Tutorials
      • Case study: End-to-end processing of a ligand-bound GPCR (EMPIAR-10853)
      • Case Study: DkTx-bound TRPV1 (EMPIAR-10059)
      • Case Study: Pseudosymmetry in TRPV5 and Calmodulin (EMPIAR-10256)
      • Case Study: End-to-end processing of an inactive GPCR (EMPIAR-10668)
      • Case Study: End-to-end processing of encapsulated ferritin (EMPIAR-10716)
      • Case Study: Exploratory data processing by Oliver Clarke
      • Tutorial: Tips for Membrane Protein Structures
      • Tutorial: Common CryoSPARC Plots
      • Tutorial: Negative Stain Data
      • Tutorial: Phase Plate Data
      • Tutorial: EER File Support
      • Tutorial: EPU AFIS Beam Shift Import
      • Tutorial: Patch Motion and Patch CTF
      • Tutorial: Float16 Support
      • Tutorial: Particle Picking Calibration
      • Tutorial: Blob Picker Tuner
      • Tutorial: Helical Processing using EMPIAR-10031 (MAVS)
      • Tutorial: Maximum Box Sizes for Refinement
      • Tutorial: CTF Refinement
      • Tutorial: Ewald Sphere Correction
      • Tutorial: Symmetry Relaxation
      • Tutorial: Orientation Diagnostics
      • Tutorial: BILD files in CryoSPARC v4.4+
      • Tutorial: Mask Creation
      • Case Study: Yeast U4/U6.U5 tri-snRNP
      • Tutorial: 3D Classification
      • Tutorial: 3D Variability Analysis (Part One)
      • Tutorial: 3D Variability Analysis (Part Two)
      • Tutorial: 3D Flexible Refinement
        • Installing 3DFlex Dependencies (v4.1–v4.3)
      • Tutorial: 3D Flex Mesh Preparation
    • Webinar Recordings
  • Real-time processing in cryoSPARC Live
    • About CryoSPARC Live
    • Prerequisites and Compute Resources Setup
    • How to Access cryoSPARC Live
    • UI Overview
    • New Live Session: Start to Finish Guide
    • CryoSPARC Live Tutorial Videos
    • Live Jobs and Session-Level Functions
    • Performance Metrics
    • Managing a CryoSPARC Live Session from the CLI
    • FAQs and Troubleshooting
  • Guides for v3
    • v3 User Interface Guide
      • Dashboard
      • Project and Workspace Management
      • Create and Build Jobs
      • Queue Job, Inspect Job and Other Job Actions
      • View and Download Results
      • Job Relationships
      • Resource Manager
      • User Management
    • Tutorial: Job Builder
    • Get Started with CryoSPARC: Introductory Tutorial (v3)
    • Tutorial: Manually Curate Exposures (v3)
  • Resources
    • Questions and Support
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On this page
  • Overview
  • cryosparcm test install
  • Example Output
  • Test Checklist
  • cryosparcm test workers
  • Usage
  • Example Output
  • Launch Test
  • SSD Test
  • GPU Test
  1. Setup, Configuration and Management
  2. Software System Guides

Guide: Installation Testing with cryosparcm test

This guide covers how to use cryosparcm test to verify your CryoSPARC installation is working properly.

PreviousGuide: Updating to CryoSPARC v4NextGuide: Verify CryoSPARC Installation with the Extensive Validation Job (v4.3+)

Last updated 1 year ago

The information in this section applies to CryoSPARC v4.0+.

Overview

After installing CryoSPARC , you can verify your instance is correctly installed by using cryosparcm test install and cryosparcm test workers via the command line. Running these functions will perform several tests that ensure users can seamlessly launch jobs and process data in CryoSPARC.

cryosparcm test install

This function tests the core components of CryoSPARC (HTTP connections, licensing, workers, etc.) that are required to start running jobs and provides information on the status of the CryoSPARC instance (e.g., which version is running, whether a patch is available, etc.).

To run this function, log into a shell on the master node as the user that owns the CryoSPARC instance.

Run cryosparcm test -h for full usage instructions.

Example Output

cryosparcuser@uoft ~/ $ cryosparcm test i
Running installation tests...
✓ Running as cryoSPARC owner
✓ Running on master node
✓ CryoSPARC is running
✓ Connected to command_core at http://uoft:63582
✓ CRYOSPARC_LICENSE_ID environment variable is set
✓ License has correct format
✓ Insecure mode is disabled
✓ License server set to "https://get.cryosparc.com"
✓ Connection to license server succeeded
✓ License server returned success status code 200
✓ License server returned valid JSON response
✓ License exists and is valid
✓ CryoSPARC is running v4.0.0
✓ Running the latest version of cryoSPARC
✓ Patch update not required
✓ Admin user has been created
✓ GPU worker connected

Test Checklist

Running cryosparcm test install will test or check the following components:

  1. Test if the cryosparcm test install command is running as the user who owns the CryoSPARC instance.

  2. Test if the cryosparcm test install command is running on the machine that runs the CryoSPARC master instance.

  3. Check if the CryoSPARC instance is turned on.

    • If this test fails, turn on CryoSPARC by running cryosparcm start and run the command again.

  4. Test if an HTTP connection can be successfully created to the command_core (CRYOSPARC_BASE_PORT+2) server.

  5. Check if the environment variable CRYOSPARC_LICENSE_ID is set.

  6. Test if the CryoSPARC License ID is in the correct format.

    1. If this test fails, ensure the CryoSPARC License ID found in cryosparc_master/config.sh is set to the correct license ID.

  7. Check if insecure request mode is enabled or disabled.

    1. This option is controlled by the CRYOSPARC_INSECURE environment variable found in cryosparc_master/config.sh.

    2. Enabling this option ignores SSL certificate errors when connecting to HTTPS endpoints. This is useful if you are behind an enterprise network using SSL injection.

  8. Check if the URL to the license server is valid.

    1. The URL can be overridden by the CRYOSPARC_LICENSE_SERVER_ADDR environment variable found in cryosparc_master/config.sh.

  9. Check if the CryoSPARC License ID being used is active.

    1. If this test fails, either the CryoSPARC instance wasn’t able to connect to the licensing server, the license isn’t active, or there was a network partition causing data corruption (in which case, trying the command again in a few minutes may fix the issue).

  10. Check the current running version of the CryoSPARC instance.

  11. Check if there is an update available for CryoSPARC.

  12. Check if there is a patch update available for CryoSPARC.

  13. Check if a worker is connected with at least one GPU.

cryosparcm test workers

This function tests workers connected to CryoSPARC to ensure they can correctly run CryoSPARC jobs by testing if the worker can launch jobs, cache particles to an SSD (if an SSD is configured), and utilize the GPU correctly. This test can be run via the command line, or directly in the CryoSPARC user interface. Three new jobs have been added to CryoSPARC that can be run at any time on the lane you’d like to test.

Usage

Run cryosparcm test -h for full usage instructions.

The tests require a project to be run inside. If there are no projects in the instance, create one before running this function.

To run all tests on all workers:

  • run cryosparcm test workers <project_uid>

  • (e.g., cryosparcm test workers P1)

To run only the GPU test on all workers:

  • run cryosparcm test workers <project_uid> --test gpu

  • (e.g., cryosparcm test workers P1 --test gpu).

To run only the GPU test on a single worker:

  • run cryosparcm test workers <project_uid> --test gpu --target <workstation_hostname>

  • (e.g., cryosparcm test workers P1 --test gpu --target cryoem1.uoft.ca)

To run only the GPU test (with Tensorflow and PyTorch) on a single worker:

  • run cryosparcm test workers <project_uid> --test gpu --test-tensorflow --test-pytorch --target <workstation_hostname>

  • (e.g., cryosparcm test workers P1 --test gpu --test-tensorflow --test-pytorch --target cryoem1.uoft.ca)

To run only the GPU test on two workers:

  • run cryosparcm test workers <project_uid> --test gpu --target <workstation1_hostname> --target <workstation2_hostname>

  • (e.g., cryosparcm test workers P1 --test gpu --target cryoem1.uoft.ca --target cryoem2.uoft.ca)

Example Output

Some text removed for readability.

cryossparcuser@uoft ~/ $ cryosparcm test workers P1
Using project P1
Running worker tests...
Worker test results
cryoem3
  ✓ LAUNCH
  ✓ SSD
  ✓ GPU
cryoem2
  ✓ LAUNCH
  ✓ SSD
  ✓ GPU
cryoem5
  ✓ LAUNCH
  ✕ SSD
    Error: [Errno 13] Permission denied: '/scratch'
    See P1 J1211 for more information
  ⚠ GPU
    No GPU available
cryoem6
  ✕ LAUNCH
    Error: 
    See P1 J1203 for more information
  ⚠ SSD
    Did not run: Launch test failed
  ⚠ GPU
    Did not run: Launch test failed
cryoem1
  ✓ LAUNCH
  ✓ SSD
  ✓ GPU
    ⚠ RTX A6000 @ 00000000:03:00.0: Persistence Mode is Disabled. 
      Enable Persistence mode by running `nvidia-smi -pm 1` as root to persist 
      the NVIDIA driver, reducing GPU load times.
    ⚠ RTX A6000 @ 00000000:03:00.0: GPU Software Power Cap is Active
    ⚠ RTX A6000 @ 00000000:21:00.0: Persistence Mode is Disabled. 
      Enable Persistence mode by running `nvidia-smi -pm 1` as root to persist 
      the NVIDIA driver, reducing GPU load times.
    ⚠ RTX A6000 @ 00000000:21:00.0: GPU Software Power Cap is Active
    ⚠ GeForce RTX 3090 @ 00000000:4C:00.0: Persistence Mode is Disabled. 
      Enable Persistence mode by running `nvidia-smi -pm 1` as root to persist 
      the NVIDIA driver, reducing GPU load times.
cryoem7
  ✓ LAUNCH
  ✓ SSD
  ✓ GPU
cryoem9
  ✓ LAUNCH
  ✓ SSD
  ✕ GPU
    Error: Tensorflow detected 0 of 7 GPUs.
    See P1 J1222 for more information
cryoem10
  ✓ LAUNCH
  ✓ SSD
  ✓ GPU

When the worker test is run, a new workspace inside the specified project will be created to contain all test jobs. The workspace will be named with the date and time (UTC) of execution.

Launch Test

Note that if a launch test fails on a worker, the SSD and GPU tests will not run:

cryoem6
  ✕ LAUNCH
    Error: ssh: connect to host cryoem6 port 22: No route to host
    See P1 J1203 for more information
  ⚠ SSD
    Did not run: Launch test failed
  ⚠ GPU
    Did not run: Launch test failed

SSD Test

If an SSD is configured for a worker, the SSD test will confirm that particle caching is working properly. The test creates five different particle stacks of shape (500, 512, 512) in the project directory, and tries to cache them to the SSD.

Testing SSD

Generating a 500 particle stack with shape (512, 512).

Writing particle stack 1/5... Done in 1.517s
Writing particle stack 2/5... Done in 1.329s.
Writing particle stack 3/5... Done in 1.290s.
Writing particle stack 4/5... Done in 1.221s.
Writing particle stack 5/5... Done in 1.219s.

Loading a ParticleStack with 5 items...
 SSD cache : cache successfully synced in_use
 SSD cache : cache successfully synced, found 233127.92MB of files on SSD.
 SSD cache : cache successfully requested to check 5 files.
 SSD cache : cache requires 2500.00MB more on the SSD for files to be downloaded.
 SSD cache : cache has enough available space.

 Transferring J33/data/simulated_particles_4.mrc (500 MB) (5/5)
  Complete      :         2500 MB (100.00%)
  Total         :         2500 MB
  Current Speed :    1133.22 MB/s
  Average Speed :    1089.09 MB/s
  ETA           :      0h  0m  0s

 SSD cache : complete, all requested files are available on SSD.
Done.

Cleaning up testing data...
SSD Test completed successfully.

If an SSD Test fails for any reason, the reason will be summarized in the test results:

cryoem5
  ✓ LAUNCH
  ✕ SSD
    Error: [Errno 13] Permission denied: '/scratch'
    See P1 J1211 for more information
  ⚠ GPU
    No GPU available

GPU Test

The GPU test will collect information about all the GPUs on the worker and test if the worker can compile and run GPU code.

The following information is collected about each GPU via nvidia-smi:

  • driver_version: GPU driver version

    • keeping the driver up to date ensures stability

  • persistence_mode: GPU driver persistence

    • enabling this reduces GPU driver load times

    • enable this by running nvidia-smi --pm 1 as root

  • power_limit: GPU power limit (TDP)

    • information only

  • sw_power_limit: software power limiter

    • if “Active”, this might indicate the power supply unit (PSU) on the workstation isn’t able to support the power draw from the GPU, or if a power supply cable is faulty or not properly connected to the GPU

    • if “Active”, this might indicate the GPU temperature is too high

  • hw_power_limit: hardware power limiter

    • if “Active”, this might indicate the power supply unit (PSU) on the workstation isn’t able to support the power draw from the GPU

    • if “Active”, this might indicate the GPU temperature is too high

  • compute_mode: current compute mode (Default, Exclusive Process, etc.)

    • the “exclusive process” compute mode prevents a process from obtaining a context from a GPU while another process already has one, useful in anonymous multi-user scenarios

    • set the compute mode of the GPU by running nvidia-smi -c compute_mode -i target_gpu_id where compute_mode is one of:

      • 0/Default, 1/Exclusive Thread, 2/Prohibited, 3/Exclusive Process

  • max_pcie_link_gen: maximum PCIe link generation (e.g., PCIe 3 or PCIe 4)

    • information only

  • current_pcie_link_gen: current PCIe link generation

    • information only

    • this may be equal to or lower than the max_pcie_link_gen, as the GPU automatically switches to a higher link under load

  • temperature: current temperature

    • information only

  • gpu_utilization: current utilization

    • information only

  • memory_utilization: current memory utilization

    • information only

Example data:

Obtaining GPU info via `nvidia-smi`...

NVIDIA GeForce RTX 3090 @ 00000000:01:00.0
    driver_version                :510.68.02
    persistence_mode              :Enabled
    power_limit                   :350.00
    sw_power_limit                :Not Active
    hw_power_limit                :Not Active
    compute_mode                  :Default
    max_pcie_link_gen             :4
    current_pcie_link_gen         :1
    temperature                   :25
    gpu_utilization               :0
    memory_utilization            :0

NVIDIA A100-PCIE-40GB @ 00000000:61:00.0
    driver_version                :510.68.02
    persistence_mode              :Enabled
    power_limit                   :250.00
    sw_power_limit                :Not Active
    hw_power_limit                :Not Active
    compute_mode                  :Default
    max_pcie_link_gen             :4
    current_pcie_link_gen         :4
    temperature                   :33
    gpu_utilization               :0
    memory_utilization            :0

Starting PyCuda GPU test on: NVIDIA A100-PCIE-40GB @ 0000:61:00.0
    PyCuda was compiled with CUDA: (11, 2, 0)
Finished PyCuda GPU test in 0.026s

Testing Tensorflow...
    Tensorflow found 4 GPUs.
Tensorflow test completed in 3.385s
cryoem9
  ✓ LAUNCH
  ✓ SSD
  ✕ GPU
    Error: Tensorflow detected 0 of 7 GPUs.
    See P1 J1222 for more information

Testing Tensorflow and PyTorch

By default, Tensorflow and PyTorch capabilities are not tested during the GPU test. To enable these tests, specify --test-tensorflow and/or --test-pytorch when starting the worker test. For example:

cryosparcm test workers P12 --test-tensorflow --target cryoem9.structura.dev

The PyTorch test will fail if the 3D Flex Refine dependencies were not installed using cryosparcw install-3dflex introduced in CryoSPARC v4.1.0. For more information, see <Link to 3D Flex Refine: Installing Dependencies>

If Tensorflow or PyTorch was not able to detect all GPUs on your system, the job will fail, and the error message will appear in the job's stdout log (found in the 'Metadata' tab of the Job Dialog).

If this test fails, ensure a firewall isn’t blocking access to the ten consecutive ports from CRYOSPARC_BASE_PORT (default 39000, e.g., 39000-39010). For more information, see in the Guide.

The default URL is

If the instance is having trouble connecting to the licensing server, see in the Guide. Additionally, if your network is behind an HTTP proxy, see in the Guide.

If the license being used is no longer active, request a new CryoSPARC License ID. See in the Guide.

See the .

To update CryoSPARC, run cryosparcm update. For more information, see in the Guide.

To patch CryoSPARC, run cryosparcm patch. For more information, see in the Guide.

To add a GPU worker to CryoSPARC, see in the Guide.

If a test job fails, check the job's Event Log and for more details.

The ability to launch jobs will be tested first. This will indicate if the worker is accessible and can correctly run CryoSPARC jobs. If this test fails, it most likely indicates a connection issue between the master and the worker. For more information, see in the Guide.

For more information on configuring and troubleshooting an SSD cache for a worker, see in the Guide.

the “default” compute mode allows users to launch multiple GPU jobs onto the same GPU via the Queue modal in the UI. See in the Guide.

Finally, PyCUDA (and optionally Tensorflow and PyTorch) will be tested to ensure they are working properly. If the either of these tests fail, the error will be summarized in the test results. For more information, check the failed job’s Event Log and .

using the instructions here
Open TCP Ports
https://get.cryosparc.com
License Server Troubleshooting
Custom SSL Certificate Authority Bundle
Obtaining A License ID
CryoSPARC Changelog
Software Updates and Patches
Apply Patches
Connecting A Worker Node
stdout log (joblog)
Cannot Queue or Run Job
SSD Particle Caching in CryoSPARC
NVIDIA Driver Downloads
NVIDIA Docs: Driver Persistence
Queuing Directly To A GPU
stdout log (joblog)
You can find the jobs used for worker tests in the "Instance Testing Utilities" section of the job builder.
Workspace card of an instance testing run.