This article briefly describes the steps for running Altair EDEM on a virtual machine (VM) that's deployed on Azure. It also presents the performance results of running EDEM on Azure.
EDEM is a high-performance application that's used for bulk material simulation. EDEM uses discrete element method (DEM) to simulate and analyze the behavior of coal, mined ores, soils, fibers, grains, tablets, and powders. EDEM:
- Provides crucial insight into bulk material interaction with equipment during a range of operation and process conditions.
- Creates simulations of real-world materials like large rocks, fine powders, grains, fibers, and tablets, representing material behaviors like dry, sticky, and compressible.
EDEM includes three core components: EDEM Creator, Simulator, and Analyst.
EDEM is primarily used in industries like construction (facilities), off-highway, mining (energy), agriculture, space exploration (aerospace), and process/manufacturing.
Why deploy EDEM on Azure?
- Modern and diverse compute options to align to your workload's needs
- The flexibility of virtualization without the need to buy and maintain physical hardware
- Rapid provisioning
- Ability to solve simulations in a few hours (with A100 GPUs)
Architecture
Download a Visio file of this architecture.
Components
- Azure Virtual
Machines is
used to create Windows VMs.
- For information about deploying the VM and installing the drivers, see Windows VMs on Azure.
- Azure Virtual
Network is
used to create a private network infrastructure in the cloud.
- Network security groups are used to restrict access to the VMs.
- A public IP address connects the internet to the VM.
- A physical SSD is used for storage.
Compute sizing and drivers
Performance tests of EDEM on Azure used ND A100 v4 and NCv3 series VMs running the Windows operating system. The following table provides the configuration details.
| VM size | vCPU | Memory, in GiB | Temporary storage (SSD), in GiB | GPUs | GPU memory, in GiB | Maximum data disks |
|---|---|---|---|---|---|---|
| Standard_ND96asr_v4 | 96 | 900 | 6,000 | 8 A100 | 40 | 32 |
| Standard_NC6s_v3 | 6 | 112 | 736 | 1 V100 | 16 | 12 |
Required drivers
To use EDEM on Standard_ND96asr_v4 VMs, you need to install NVIDIA and AMD drivers.
To use EDEM on Standard_NC6s_v3 VMs, you need to install NVIDIA drivers.
EDEM installation
Before you install EDEM, you need to deploy and connect a VM, install an eligible Windows 10 or Windows 11 image, and install the NVIDIA drivers. On Standard_ND96asr_v4 VMs, you need to install the AMD drivers.
For information about eligible Windows images, see How to deploy Windows 10 on Azure and Use Windows client in Azure for dev/test scenarios.
Important
NVIDIA Fabric Manager installation is required for VMs that use NVLink or NVSwitch.
For information about deploying the VM and installing the drivers, see Run a Windows VM on Azure.
To install EDEM, you need to download EDEM from Altair One Marketplace, install License Manager, and then install EDEM. For detailed installation instructions, see Altair One Marketplace.
EDEM performance results
Seven real-world scenarios were used to test the performance of EDEM on Azure VMs. Particle simulations were tested. The following table provides the details.
| Model | Angle of repose | Bed of material | Hopper discharge | Powder mixer | Screw augur | Mill | Transfer chute |
|---|---|---|---|---|---|---|---|
| Description | Cylinder angle of repose | Bed of material with tillage tool | Hopper emptying into container | Powder mixer operation | Screw augur operation | Mill operation | Transfer chute with dynamic factory |
 |
 |
 |
 |
 |
 |
 |
|
| Particle radius (m) | 0.0005 - 0.001 | 0.002 - 0.004 | 0.003 | 0.0005 | 0.001 | 0.005 | 0.0045 - 0.009 |
| Number of spheres | 3 | 3 | 3 | 1 | 1 | 1 | 3 |
| Size distribution | Random | Random | Fixed | Fixed | Fixed | Fixed | Random |
| Number of particles | 1,000,000 | 1,000,000 | 1,000,000 | 1,000,000 | 1,000,000 | 1,000,000 | 1,000,000 |
| Physics | Hertz-Mindlin | Hertz-Mindlin with JKR | Hertz-Mindlin | Hertz-Mindlin | Hertz-Mindlin | Hertz-Mindlin | Hertz-Mindlin with JKR |
| Time steps | 5.73E-06 | 5.00E-05 | 4.00E-05 | 9.20E-06 | 1.40E-05 | 0.00016 | 5.97E-05 |
| Total time | 0.5 | 1 | 1 | 1 | 1 | 1 | 1 |
| Save interval | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 |
| Grid cell size (x Rmin) | 3 | 3 | 3 | 3 | 3 | 3 | 5 |
| Factory | No | No | No | No | No | No | Yes |
| Periodic boundaries | No | No | No | No | No | No | No |
The following table shows the elapsed wall-clock time required to complete each of the simulations, in seconds.
| Model | 96 CPUs | 8 A100 GPUs (ND96asr_v4) | V100 GPU (NC6s_v3) |
|---|---|---|---|
| Angle of repose | 12819.80 | 1543.66 | 2319.39 |
| Bed of material | 2650.56 | 320.24 | 475.04 |
| Hopper discharge | 9318.89 | 566.59 | 1030.38 |
| Powder mixer | 14028.50 | 1013.98 | 1312.27 |
| Screw auger | 8871.59 | 1295.16 | 1158.98 |
| Mill | 1339.11 | 83.18 | 116.49 |
| Transfer chute | 3859.01 | 310.22 | 437.92 |
This graph shows the elapsed seconds for A100 GPUs, compared to the results for 96 CPUs.
The following table shows the relative speed increases for A100 GPUs and the V100 GPU, as compared to 96 CPUs.
| Model | 96 CPUs | 8 A100 GPUs (ND96asr_v4) | V100 GPU (NC6s_v3) |
|---|---|---|---|
| Angle of repose | 1 | 8.30 | 5.53 |
| Bed of material | 1 | 8.28 | 5.58 |
| Hopper discharge | 1 | 16.45 | 9.04 |
| Powder mixer | 1 | 13.84 | 10.69 |
| Screw auger | 1 | 6.85 | 7.65 |
| Mill | 1 | 16.10 | 11.50 |
| Transfer chute | 1 | 12.44 | 8.81 |
This graph shows the relative speeds:
Azure cost
Only rendering time is considered for these cost calculations. Application installation time isn't considered.
You can use the wall-clock time presented in the following table and the Azure hourly rate to calculate costs. For the current hourly costs, see Windows Virtual Machines Pricing.
You can use the Azure pricing calculator to estimate the costs for your configuration.
| VM size | Model | Wall-clock time, in seconds |
|---|---|---|
| Standard_ND96asr_v4 | Angle of repose | 1543.66 |
| Standard_ND96asr_v4 | Bed of material | 320.244 |
| Standard_ND96asr_v4 | Hopper discharge | 566.587 |
| Standard_ND96asr_v4 | Powder mixer | 1013.98 |
| Standard_ND96asr_v4 | Screw auger | 1295.16 |
| Standard_ND96asr_v4 | Mill | 83.1794 |
| Standard_ND96asr_v4 | Transfer chute | 310.224 |
| Standard_NC6s_v3 | Angle of repose | 2319.39 |
| Standard_NC6s_v3 | Bed of material | 475.04 |
| Standard_NC6s_v3 | Hopper discharge | 1030.38 |
| Standard_NC6s_v3 | Powder mixer | 1312.27 |
| Standard_NC6s_v3 | Screw auger | 1158.98 |
| Standard_NC6s_v3 | Mill | 116.49 |
| Standard_NC6s_v3 | Transfer chute | 437.92 |
Summary
- Altair EDEM was successfully tested on ND A100 v4 and NCv3 series VMs on Azure.
- The highest speeds are achieved on ND96asr_v4 VMs.
- Simulations for complex workloads are solved in a few hours on ND96asr_v4 VMs.
Contributors
This article is maintained by Microsoft. It was originally written by the following contributors.
Principal authors:
- Hari Bagudu | Senior Manager
- Gauhar Junnarkar | Principal Program Manager
- Vinod Pamulapati | HPC Performance Engineer
Other contributors:
- Mick Alberts | Technical Writer
- Guy Bursell | Director Business Strategy
- Sachin Rastogi | Manager
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Next steps
- GPU-optimized virtual machine sizes
- Windows virtual machines on Azure
- Virtual networks and virtual machines on Azure
- Learning path: Run high-performance computing (HPC) applications on Azure