Hardware Recommendations and Certifications

View the most recent recommended graphic boards, laptops and desktop hardware configurations.

Recommended Graphics Boards

Recommended CAE/CAD graphic boards to use with Altair Simulation applications.

The most recent vendor/manufacturer drivers should be used and all driver support for these cards should be addressed to the appropriate manufacturer of the graphic board.
Note: AMD graphics cards will no longer be supported on Linux x86_64 operating systems in Altair Simulation 2022 and higher products.

AMD Graphics Cards

Products GPU Model Driver Version
Radeon™ Pro W6800

W6600

VII

WX 9100

W5700

WX 8200

W5500

WX 7100

WX 5100

WX 4100

WX 3200

WX 3100

WX 2100
Windows 10 (64-bit)
22.Q4
Linux (64-bit)
Not Supported
Radeon™ Pro Mobility WX 7130

WX 7100

WX 4170

WX 4150

WX 4130

WX 3100

WX 2100
Windows 10 (64-bit)
22.Q4
Linux (64-bit)
Not Supported

NVIDIA Graphics Boards

Products GPU Model Driver Version
M

(Maxwell)

 P

(Pascal)

 V

(Volta)

 RTX

(Turing)

 A*

(Ampere)

 ADA Generation
Quadro Series M2000

M4000

M5000

M6000

 P400

P420

P600

P620

P1000

P2000

P2200

P4000

P5000

P5200

P6000

GP100

 GV100 RTX 3000

RTX 4000

RTX 5000

RTX 6000

RTX 8000

T400

T600

T1000

 RTX A2000

RTX A3000

RTX A4000

RTX A5000

RTX A6000

 RTX 6000 ADA
Windows 10 (64-bit)
R525 U5 (528.49)
Linux (64-bit) ODE Long Live
525.89.02
Quadro Mobility M500M

M520M

M600M

M620M

M1000M

M2000M

M2200M

M3000M

M4000M

M5000M

 P500

P520

P600

P620

P1000

P2000

P3000

P3200

P4000

P4200

P5000

P5200

 N/A T400

T600

T1000

T1200

T2000

RTX 3000

RTX 4000

RTX 5000

 RTX A2000

RTX A3000

RTX A4000

RTX A5000

  
Windows 10 (64-bit)
R525 U5 (528.49)
Linux (64-bit) ODE Long Live
525.89.02
Note:
Minimum OpenGL 3.2 and OpenCL 2.1 Requirement
Virtual server/clients and VirtualGL setups may work, but are not officially tested or supported.
NVIDIA Optimus or AMD Switchable Graphics
In order to ensure best performance, these options should be set to use discrete NVIDIA or AMD GPU and not the Intel GPU.
Power Options and Mobility Center
In order to ensure best performance, these options should be maximum performance for both GPU and CPU.
Graphics Driver Corruption or Installation Issues
In order to ensure best driver compatibility, it is recommended to use “Custom” and “Clean” install options instead of the general “Express” driver installer options.

Recommended Workstation Desktop and Laptop/Notebook Hardware

DELL Workstations - Desktops

Product Precision Workstation
Workstation Model NVIDIA Quadro GPU AMD Radeon™ Pro GPU
3260C T400

T600

T1000

RTX A2000

RTX 3000

  
3450 SFF P400

P620

P1000

T400

T600

T1000

 WX3200
3460 (mini) RTX 3000 N/A
3460 SFF T400

T600

T1000

RTX A2000

  
3650 P400

P620

P1000

P2200

T400

T600

T1000

RTX 4000

RTX 5000

RTX A2000

RTX A4000

RTX A5000

RTX A6000

W5500

W5700

W6600

W6800

WX3200
3660T T400

T600

T1000

RTX A2000

RTX A4000

RTX A4500

RTX A5000

RTX A5500

RTX A6000

  
5860T T400

T1000

RTX A2000

RTX A4000

RTX A4500

RTX A5000

RTX A5500

RTX A6000

GV100

  
7865T T400

T1000

RTX A2000

RTX A4000

RTX A4500

RTX A5000

RTX A5500

RTX A6000

GV100

  
7960T T400

T1000

RTX A2000

RTX A4000

RTX A4500

RTX A5000

RTX A5500

RTX A6000

GV100

  
7960 Rack T400

T1000

RTX A2000

RTX A4000

RTX A4500

RTX A5000

RTX A5500

RTX A6000

GV100

  

DELL Workstations - Laptops

Product Precision Workstation
Workstation Model NVIDIA Quadro GPU AMD Radeon™ Pro GPU
3470 T550 N/A
3550 P520 N/A
3551 P620 N/A
3560 T500 N/A
3561 T600

T1200

 N/A
3570 T550

T600

RTX A500

 N/A
3571 T600

RTX A1000

RTX A2000

 N/A
5470 RTX A1000 N/A
5540 / 5740 T1000

T2000

RTX 3000*

 N/A
5550 / 5750* T1000

T2000

RTX 3000*

 N/A
5560 T1200

RTX A2000

 N/A
5570 RTX A1000

RTX A2000

 N/A
5760 RTX A2000

RTX A3000

 N/A
5770 RTX A2000

RTX A3000

  
7540 / 7740 T1000

T2000

RTX 3000

RTX 4000

RTX 5000

 WX 3200

WX 7130

7550 / 7750 T1000

T2000

RTX 3000

RTX 4000

RTX 5000

 N/A
7560 T1200

RTX A2000

RTX A3000

RTX A4000

RTX A5000

 N/A
7670 RTX A1000

RTX A2000

RTX A3000

RTX A4500

RTX A5500

 N/A
7760 T1200

RTX A3000

RTX A4000

RTX A5000

 N/A
7770 RTX A1000

RTX A3000

RTX A4500

RTX A5500

 N/A

Lenovo Workstations - Desktops

Product Lenovo ThinkStation
Workstation Model NVIDIA Quadro GPU (442.92 or higher) AMD Radeon™ Pro GPU
P320 SFF /

P320 TWR*

 P400

P600

P1000

P2000*

P4000*

 N/A
P330 SFF /

P330 TWR*

 P400

P620

P1000

P2000*

P2200*

P4000*

 N/A
P340 SFF /

P340 TWR*

 RTX A2000*

RTX 4000*

RTX 5000*

RTX A4000*

RTX A5000*

T400

T600

T1000

 N/A
P340 Tiny T1000  
P348 T400

T600

T1000

  
P350 SFF /

P350 TWR*

 P2200

RTX A2000

RTX A4000*

RTX A5000*

T400

T600

T1000

  
P350 Tiny T600

T1000

 N/A
P358 TWR RTX A2000

T600

T1000

 N/A
P360 Ultra/

P360 TWR*

 RTX A2000

RTX A4000*

RTX A4500*

RTX A5000

RTX A5000m

T400

T600*

T1000

  
P360 Tiny T400

T1000

 N/A
P520* / P520c RTX 4000

RTX 5000

RTX 6000*

RTX A2000

RTX A4000

RTX A4500

RTX A5000

RTX A6000*

T400

T600

T1000

 N/A
P620 (AMD Ryzen PRO 3975X) /

(AMD Ryzen Threadripper PRO 5955WX)

 GP100

RTX 4000

RTX 5000

RTX 6000

RTX 8000

RTX A2000

RTX A4000

RTX A4500

RTX A5000

RTX A5500

RTX A6000

T400

T600

T1000

 W5500

W5700

P720 / P920 RTX 4000

RTX 5000

RTX 6000

RTX 8000

RTX A2000

RTX A4000

RTX A4500

RTX A5000

RTX A5500

RTX A6000

T400

T600

T1000

 N/A
NEC (mini) P1000 N/A

Lenovo Workstations - Laptops (*Windows 10 support only)

Product Workstation Model
Lenovo ThinkPad NVIDIA Quadro GPU AMD Radeon™ Pro GPU
P1

Gen1

 P1000M

P2000M

 N/A
P1

Gen2*

 T1000

T2000

 N/A
P1

Gen3

 T1000

T2000

 N/A
P1

Gen4

 T1200

RTX A2000

RTX A3000

RTX A4000

RTX A5000

 N/A
P1

Gen5

 RTX A1000

RTX A2000

RTX A3000

RTX A4500

RTX A5500

 N/A
P14s P520 N/A
P14s

Gen1

 P520 AMD Ryzen 7 PRO 4750U with Radeon Graphics (2 GB)

AMD APU 4400
P14s

Gen2

 T500 AMD APU 5500
P14s

Gen3a

 N/A Radeon PRO Graphics
P14s

Gen3i

 T550 N/A
P15

Gen1

 T1000

T2000

RTX 3000

RTX 4000

 N/A
P15

Gen2

 T1200

RTX A2000

RTX A3000

RTX A4000

RTX A5000

 N/A
P15s

Gen1

 P520 N/A
P15s

Gen2

 T500  
P15v

Gen1

 P620 N/A
P15v

Gen2

 T600

T1200

RTX A2000

 N/A
P15v

Gen3a/Gen3i

 T600

T1200

RTX A2000

 N/A
P16

Gen1

 RTX A1000

RTX A2000

RTX A3000

RTX A4500

RTX A5500

 N/A
P16s

Gen1a

 N/A Radeon PRO Graphics
P16s

Gen1i

 T550 N/A
P17

Gen1

 T1000

T2000

RTX 3000

RTX 4000

RTX 5000

 N/A
P17

Gen2

 T1200

RTX A2000

RTX A3000

RTX A4000

RTX A5000

 N/A
P40

Yoga

 M500M N/A
P43s* P520 N/A
P50 M1000M

M2000M

 N/A
P50s M500M N/A
P51 M1200M

M2200M

 N/A
P51s M520M N/A
P52 P1000

P2000

P3200

 N/A
P52s P500 N/A
P53* T1000

T2000

RTX 3000

RTX 4000

 N/A
P53s* P520 N/A
P71 M620M

P3000

P4000

P5000

 N/A
P72 P600

P2000

P3200

P4200

P5200

 N/A
P73* P620

T2000

RTX 3000

RTX 4000

RTX 5000

 N/A

Acer Workstations and Laptops (*Windows 10 support only)

Product Acer
Workstation Model NVIDIA Quadro GPU AMD Radeon™ Pro GPU
ConceptD

500*

 RTX 4000 N/A
ConceptD

700*

 RTX 4000 N/A
Veriton

K8

 RTX 4000 N/A
Veriton

K8690G

RTX A4000 N/A
Product Acer
Mobile Workstation Model NVIDIA Quadro GPU AMD Radeon™ Pro GPU
ConceptD 3

Pro*

 T1000 N/A
ConceptD 3

Ezel Pro*

 T1000 N/A
ConceptD 5

Pro*

 RTX 3000 N/A
ConceptD 7

Pro*

 RTX 3000 N/A
ConceptD 7

Ezel Pro*

 RTX 5000 N/A

Altos Workstations and Laptops (*Windows 10 support only)

Product Altos

Computing
Workstation Model NVIDIA Quadro GPU AMD Radeon™ Pro GPU
BrainSphere™

P130 F5

 RTX 2000 N/A
BrainSphere™

P530 F4

 K420

P400

K620

K1200

P1000

P2000

P4000

P5000

P6000

GP100

RTX 2000

RTX 4000

RTX 5000

 N/A

SuperMicro Workstations

Product SuperMicro
System Model

AS- 5014A-TT

 NVIDIA Quadro GPU AMD Radeon™ Pro GPU
Mainstream

Ryzen Threadripper Pro 3955WX

 RTX A4500 W6800
Performance

Ryzen Threadripper Pro 3975WX

 RTX A4500 W6800
Expert

Ryzen Threadripper Pro 3995WX

 RTX A4500 W6800
  (visit SuperMicro for a complete GPU support list)

Comments

For NVIDIA GPU based laptops/notebooks the Optimus power saving option in the BIOS should be disabled and the NVIDIA drivers properly installed for optimal performance in Altair Simulation products.

For AMD GPU based laptops/notebooks; the Enduro/Switchable Graphics power saving option should be disabled and the AMD drivers properly installed for optimal performance in Altair Simulation products.

Optimus (Intel/NVIDIA) enabled drivers may create performance issues with notebooks/laptops compared to a dedicated non-shared GPU driver. Disabling the Optimus feature in BIOS, if available, will help give the best overall graphics performance.

Disable nView Window manager under NVIDIA drivers if you experience random crashes and/or issues.

All power saving modes, settings and governors for CPU frequencies and GPU performance should be set to maximum settings in order to get the optimal performance out of Altair Simulation products. This includes smooth graphics and high frame rates (FPS) on Windows and Linux platforms.

Altair Simulation 2022.3 Solver Hardware Configuration Recommendations

Recommended hardware configurations for Altair Solvers.

AcuSolve Solver

Table 1.
Problem Size Small Medium Large
Typical Workload

Steady State or Transient

 Steady state: Up to 1M nodes

Transient: Up to 100K nodes

 Steady state: Up to 10M nodes

Transient: Up to 1M nodes

 Steady state: Greater than 10M nodes

Transient: Greater than 1M nodes
Throughput 1 Single job Single job Single job
CPU 2 Dual CPU socket

For example, Intel Xeon Gold “Cascade Lake” or “Ice Lake” or AMD EPYC 7002 or 7003 series

 Dual CPU socket

For example, Intel Xeon Gold “Cascade Lake” or “Ice Lake” or AMD EPYC 7002 or 7003 series

 Dual CPU socket

For example, Intel Xeon Gold “Cascade Lake” or “Ice Lake” or AMD EPYC 7002 or 7003 series
Number of CPU / node 1-4 1-4 1-4
Number of cores / node 32 – 128 32 – 128 32 – 128
Number of nodes 1-8 8 – 48 >48
Minimum Memory Configuration / node 3 300MB to 3GB 3GB to 30GB More than 30GB

(3KB per CFD node)
Storage (minimum) 500 GB SATA or SSD 1.5 TB local storage 1.5 TB local storage
Network Interconnect Gigabit Ethernet Or Infiniband Infiniband Infiniband
Operating System Linux kernel 2.6.32 or higher

Windows 7 or 10

 Linux kernel 2.6.32 or higher Linux kernel 2.6.32 or higher
GPU Yes Yes Yes
MPI Intel MPI 2018.4 or higher Intel MPI 2018.4 or higher Intel MPI 2018.4 or higher
Setup

(2000-3000 computational nodes per core)

 Pure OpenMP or Hybrid OpenMP/MPI Hybrid OpenMP/MPI Hybrid OpenMP/MPI
Hyper Threading Not recommended Not recommended Not recommended

Feko Solver

Table 2.
Problem Size Small Medium Large
General recommendations given for MoM and MLFMM dependent on problem size in terms of number of unknowns / mesh elements. For other solution methods (FEM, FDTD, RL-GO, PO, UTD) many factors to be considered. Pure MoM: less than 50k unknowns.

MLFMM: between 100k and 500k unknowns

 Pure MoM: between 50k and 100k unknowns.

MLFMM: between 500k and 5M unknowns

 Pure MoM: >100k unknowns

MLFMM: >5M unknowns
Throughput 1 Single job Single large job or few jobs in parallel Single very large job or multiple jobs
CPU 2 Dual CPU socket

For example, Intel Xeon Gold “Cascade Lake” or “Ice Lake” or later

 Dual CPU socket

For example, Intel Xeon Gold “Cascade Lake” or “Ice Lake” or later

 Dual CPU socket

For example, Intel Xeon Gold “Cascade Lake” or “Ice Lake” or later
Number of CPU / node 2 2 2
Number of cores / node 32 – 56 32 – 56 32 – 56
Number of nodes 1 8 – 16 > 16
Minimum Memory Configuration / node 3 64 GB 128 GB 256 GB
Storage (minimum) 500 GB SATA or SSD 500 GB SATA or SSD 500 GB SATA or SSD
Network Interconnect Gigabit Ethernet Infiniband Infiniband
Operating System RHEL or CentOS 8.3

Windows 10

 Linux kernel 2.6.32 or higher Linux kernel 2.6.32 or higher
GPU Yes No No
MPI Intel MPI 2018.4 or higher Intel MPI 2018.4 or higher Intel MPI 2018.4 or higher
Setup Pure MPI Pure MPI Pure MPI
Hyper Threading Not recommended Not recommended Not recommended

Flux Solver

Table 3.
Problem type Small Medium Large
Typical Workload (depending on number of DOF, element type, and other factors) < 300 000 DOF Around 500 000 DOF Around 5M DOF
Throughput 1 Single Single Single
CPU 2 Dual CPU socket

For example, Intel Xeon Gold “Cascade Lake” or “Ice Lake”

 Dual CPU socket

For example, Intel Xeon Gold “Cascade Lake” or “Ice Lake”

 Dual CPU socket

For example, Intel Xeon Gold “Cascade Lake” or “Ice Lake”
Number of CPU / node 1 2 2
Number of cores / node 8 16 16+
Number of nodes 1 1 1-4
Minimum Memory Configuration / node 3 8 GB 16-32 GB 300GB
Storage (minimum) 500 GB SATA or SSD 1 TB local storage SSD 1.5 TB local storage SSD
Network Interconnect Infiniband
Operating System Linux kernel 3.10.0-693 or higher

Windows 7 or 10 with SSD

 Linux kernel 3.10.0-693 or higher

Windows 7 or 10 with SSD

 Linux kernel 3.10.0-693 or higher

Windows 7 or 10 with SSD
GPU No No No
MPI Intel MPI 2018.4 or higher Intel MPI 2018.4 or higher Intel MPI 2018.4 or higher
Setup SMP SMP or Hybrid 2MPI/node SMP or Hybrid 2MPI/node
Hyper Threading Not recommended Not recommended Not recommended

Radioss Solver

Table 4.
Problem Size Small Medium Large
Typical Workload

Crash & Impact

 Component tests, sled test, drop test, …

Less than 500K elements

 Medium crash model, between 1 and 6 millions of elements model Accurate car crash model (rupture), very large model with size > 6 million elements
Throughput 1 Single job Single large job or few jobs in parallel Single very large job or multiple jobs
CPU 2 Dual CPU socket

For example, Intel Xeon Gold “Cascade Lake” or “Ice Lake” or AMD EPYC 7002 or 7003 series

 Dual CPU socket

For example, Intel Xeon Gold “Cascade Lake” or “Ice Lake” or AMD EPYC 7002 or 7003 series

 Dual CPU socket

For example, Intel Xeon Gold “Cascade Lake” or “Ice Lke” or AMD EPYC 7002 or 7003 series
Number of CPU / node 2 2 2
Number of cores / node 32 – 64 32 – 128 32 – 128
Number of nodes 1 8 – 16 > 16
Minimum Memory Configuration / node 3 64-128GB 64-256GB 64-256GB
Storage (minimum) 500 GB SATA or SSD 1,5 TB local storage 1,5 TB local storage
Network Interconnect Gigabit Ethernet Infiniband Infiniband
Operating System Linux kernel 2.6.32 or higher

Windows 7 or 10

 Linux kernel 2.6.32 or higher Linux kernel 2.6.32 or higher
GPU No No No
MPI Intel MPI 2018.4 or higher Intel MPI 2018.4 or higher Intel MPI 2018.4 or higher
Setup Pure MPI Pure MPI or Hybrid with 2 or 4 OpenMP threads per MPI Hybrid with 2 or 4 OpenMP threads per MPI
Hyper Threading 5 Yes, Hybrid with 2 OpenMP per MPI Not recommended Not recommended

OptiStruct Solver

Table 5.
Problem type Small or medium Large static Large dynamic
Typical Workload (depending on number of DOF, element type, and other factors) Nonlinear - less than 2M DOF; linear static - less than 5M DOF; NVH - less than 5M DOF Nonlinear - more than 2M DOF; linear static - more than 5M DOF NVH - more than 5M DOF
Throughput 1 Single Single Single or few jobs in parallel
CPU 2 Dual CPU socket

For example, Intel Xeon Gold “Cascade Lake” or “Ice Lake”

 Dual CPU socket

For example, Intel Xeon Gold “Cascade Lake” or “Ice Lake

 Dual CPU socket

For example, Intel Xeon Gold “Cascade Lake” or “Ice Lake"
Number of CPU / node 2 2 2
Number of cores / node 8-24 24+ 24+
Number of nodes 1 1-8 1-8
Minimum Memory Configuration / node 3 16-64GB 128GB 256GB
Storage (minimum) 512GB local storage 1TB local storage 3 TB local storage, SSD and RAID0 recommended
Network Interconnect Infiniband Infiniband
Operating System Linux kernel 2.6.32 or higher

Windows 7 or 10 with SSD

 Linux kernel 2.6.32 or higher

Windows 7 or 10 with SSD

 Linux kernel 2.6.32 or higher

Windows 7 or 10 with SSD
GPU Yes Yes Yes (Eigenvalue Extraction – AMSES or Lanczos)
MPI Linux: Intel MPI 2018.4 (recommended)

Windows: Intel MPI 5.1.0.078 (recommended)

 Linux: Intel MPI 2018.4 (recommended)

Windows: Intel MPI 5.1.0.078 (recommended)

 Linux: Intel MPI 2018.4 (recommended)

Windows: Intel MPI 5.1.0.078 (recommended)
Setup SMP or DDM hybrid or SMP+GPU DDM hybrid or SMP+GPU SMP or DDM hybrid or SMP+GPU
Hyper Threading Not recommended Not recommended Not recommended

Recommended GPU Computing Processor List

Recommended graphic boards for use with the Altair Solver applications for high-powered GPU computing.

The following table lists the recommended graphic boards for use with the Altair Solver applications for high-powered GPU computing.
  Manufacturer and Model Graphics Card Driver Version

(Minimum or Higher)
AcuSolve NVIDIA

(Tesla)

 P100

V100

 Linux (64-bit)

418.39

Windows (64-bit)

396.26
NVIDIA

(Quadro)

 GP100

GV100

 Linux (64-bit)

418.39

Windows (64-bit)

396.26
OptiStruct NVIDIA

(Tesla)

 P100

V100

 Linux (64-bit)

440.33

Windows (64-bit)

441.22
NVIDIA

(Quadro)

 GP100

GV100

 Linux (64-bit)

440.33

Windows (64-bit)

441.22
Note:
  • The most recent vendor/manufacturer drivers should be used and all driver support for these cards should be addressed to the appropriate manufacturer of the graphics board.
  • Double Precision GPU cards should be used to run OptiStruct. Single precision GPU cards (such as RTX 600, etc) are not recommended for OptiStruct runs.

Additional Information on Driver Installations

The NVIDIA Driver Update recommendation is to use the Custom installation option and select the Perform clean installation option to validate that there are no conflicts in DLL/drivers.

The same should be done with AMD hardware and drivers as well using AMD’s custom uninstall tools.


Figure 1.
1 Number of simultaneous jobs. Use of a workload management middleware like Altair PBS is highly recommended to insure optimal and dedicated usage of the CPU resource
2 Typical node configuration is based on dual CPU socket processors
3 It is extremely important to populate all the memory banks on the mother board.
4 In Hybrid mode, it is recommended to set a number of MPIs that is a multiple of the number of sockets and then set the number of OpenMP in a way that number of MPIs x number of OpenMP equal number of physical cores.
5 Hyper Threading (HT) may increase performance by around 10% on single node. In this case, recommended setup is to run 2 OpenMP per MPI, with a number of MPIs that matches the total number of physical cores on the node. On multi-node, it is better not using HT