CST STUDIO SUITE R Supported GPU Hardware

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Transcription:

CST STUDIO SUITE R 2017 Supported GPU Hardware

1 Supported Hardware CST STUDIO SUITE currently supports up to 8 GPU devices in a single host system, meaning each number of GPU devices between 1 and 8 is supported. 1 The following tables contain some basic information about the GPU hardware currently supported by the GPU Computing feature of CST STUDIO SUITE, as well as the requirements for the host system equipped with the hardware. To ensure compatibility of GPU hardware and host system please check https://www.nvidia.com/object/tesla-qualified-servers.html Please note that a 64 bit computer architecture is required for GPU Computing. A general hardware recommendation can be found in the FAQ section of the CST support website (FAQ No.3908). 1 It is strongly recommended to contact CST before purchasing a system with more than four GPU cards to ensure that the hardware is working properly and is configured correctly for CST STUDIO SUITE. June 14, 2017 2

List of supported GPU hardware for CST STUDIO SUITE 2017 2 3 Card Name Series Platform Min. CST Version Tesla P100-SXM2 (Chip) Pascal Servers 2017 release Tesla P100-PCIE-16GB Pascal Servers 2017 release Tesla P100 16GB Pascal Servers 2017 release Tesla P100-PCIE-12GB Pascal Servers 2017 SP 2 Quadro P6000 4 Pascal Workstations 2017 SP 2 Quadro GP100 Pascal Workstations 2017 SP 2 Tesla M60 4 Maxwell Servers/Workst. 2016 SP 4 Tesla M40 4 Maxwell Servers 2016 SP 4 Quadro M6000 24GB 4 Maxwell Workstations 2016 SP 4 Quadro M6000 4 Maxwell Workstations 2015 SP 4 Tesla K80 Kepler Servers 2014 SP 6 Tesla K40 m/c/s/st/d/t Kepler Servers/Workst. 2013 SP 5 Quadro K6000 Kepler Workstations 2013 SP 4 Tesla K20X Kepler Servers 2013 release Tesla K20m/K20c/K20s Kepler Servers/Workst. 2013 release Tesla K10 4 Kepler Servers 2013 release Quadro 6000 5 Fermi Workstations 2012 SP 6 Tesla Fermi M-Series 5 Tesla 20/Fermi Servers 2011 SP 6 Tesla Fermi C-Series 5 Tesla 20/Fermi Workstations 2011 SP 6 Tesla M1060 5 Tesla 10 Servers 2010 SP 4 Tesla C1060 5 Tesla 10 Workstations 2010 release Quadro FX5800 5 Tesla 10 Workstations 2010 release Quadro Plex 2200D2 5 Tesla 10 Workstations 2010 release 2 Please note that cards of different series (e.g. Maxwell and Pascal ) can t be combined in a single host system for GPU Computing. 3 Platform = Servers: These GPUs are only available with a passive cooling system which only provides sufficient cooling if it s used in combination with additional fans. These fans are usually available for server chassis only! Platform = Workstations: These GPUs provide active cooling, so they are suitable for workstation computer chassis as well. 4 Important: The double precision performance of this GPU device is poor, thus, it can t be recommended for PIC-solver and I-solver (double precision) simulations. 5 Important: This hardware is marked as deprecated and won t be supported in upcoming CST STUDIO SUITE versions (2018 and newer). June 14, 2017 3

NVIDIA Tesla K20c/K20m/K20s (for Workst./Servers) NVIDIA Tesla K20X Min. CST version required 2013 release 2013 release Number of GPUs 1 1 approx. 50 million mesh cells approx. 60 million mesh cells Form Factor Dual-Slot PCI-Express Dual Slot PCI-Express Memory 5 GB GDDR5 6 GB GDDR5 Bandwidth 208 GB/s 250 GB/s Single Precision Performance 3.52 TFlops 3.95 TFlops Double Precision Performance 1.17 TFlops 1.32 TFlops Power Consumption 225 W (max.) requires two auxiliary power connectors 235 W (max.) PCI Express Requirements 1x PCIe Gen 2 (x16 electrically) 1x PCIe Gen 2 (x16 electrically) Power Supply of Host System 1 min. 750 W min. 750 W Min. RAM of Host System 2 24 GB 24 GB 1 Important: The specifications shown assume that only one adapter is plugged into the machine. If you would like to plug in two or more adapters you will need a better power supply (1000W or above) as well as more RAM. Additionally, you need to provide sufficient cooling for the machine. Each Tesla card takes power from the PCI Express host bus as well as the 8-pin and the 6-pin PCI Express power connectors. This is an important consideration while selecting power supplies. 2 The host system requires approximately 4 times as much memory as is available on the GPU cards. Although June 14, 2017 4

NVIDIA Kepler K10 1 NVIDIA Quadro K6000 Min. CST version required 2013 release 2013 SP 4 Number of GPUs 2 1 approx. 80 million mesh cells approx. 120 million cells Form Factor Dual-Slot PCI-Express Dual Slot PCI-Express Memory 8 GB GDDR5 12 GB GDDR5 Bandwidth 320 GB/s (160 GB/s per GPU) 288 GB/s Single Precision Performance 4.6 TFlops 5.2 TFlops Double Precision Performance 0.2 TFlops 1.7 TFlops Power Consumption 225 W (max.) 225 W (max.) PCI Express Requirements 1x PCIe Gen 3 (x16 electrically) 1x PCIe Gen 3 (x16 electrically) Power Supply of Host System 2 min. 750 W min. 750 W Min. RAM of Host System 3 32 GB 48 GB 1 The double precision performance of this GPU device is poor, thus, it can t be recommended for PIC-solver, A-Solver and I-solver (double precision) simulations. 2 Important: The specifications shown assume that only one adapter is plugged into the machine. If you would like to plug in two or more adapters you will need a better power supply (1000W or above) as well as more RAM. Additionally, you need to provide a sufficient cooling for the machine. Each Tesla card takes power from the PCI Express host bus as well as the 8-pin and the 6-pin PCI Express power connectors. This is an important consideration while selecting power supplies. 3 The host system requires approximately 4 times as much memory as is available on the GPU cards. Although June 14, 2017 5

NVIDIA Tesla K40m/K40c (for Servers/Workst.) NVIDIA Tesla K80 Min. CST version required 2013 SP 5 2014 SP 6 Number of GPUs 1 2 approx. 120 million mesh cells approx. 240 million mesh cells Form Factor Dual-Slot PCI-Express Dual Slot PCI-Express Memory 12 GB GDDR5 24 GB GDDR5 Bandwidth 288 GB/s 480 GB/s (240 GB/s per GPU) Single Precision Performance 1 5.04 TFlops 8.73 TFlops Double Precision Performance 1 1.68 TFlops 2.91 TFlops Power Consumption 225 W (max.) 300 W (max.) PCI Express Requirements 1x PCIe Gen 3 (x16 electrically) 1x PCIe Gen 3 (x16 electrically) Power Supply of Host System min. 750 W min. 750 W Min. RAM of Host System 2 48 GB 96 GB 1 Measured with BOOST enabled 2 The host system requires approximately 4 times as much memory as is available on the GPU cards. Although June 14, 2017 6

NVIDIA Tesla M60 1 (for Servers/Workst.) NVIDIA Tesla M40 1 Min. CST version required 2016 SP 4 2016 SP 4 Number of GPUs 2 1 Form Factor approx. 160 million mesh cells Dual-Slot PCI-Express approx. 240 million mesh cells Dual Slot PCI-Express Passive Cooling Memory 16 GB GDDR5 (8 GB x 2) 24 GB GDDR5 Bandwidth 320 GB/s (160 GB/s per GPU) 288 GB/s Single Precision Performance 9.64 TFlops 6.84 TFlops Double Precision Performance 0.301 TFlops 0.213 TFlops Power Consumption 300 W (max.) 250 W (max.) PCI Express Requirements 1x PCIe Gen 3 (x16 electrically) 1x PCIe Gen 3 (x16 electrically) Power Supply of Host System min. 750 W min. 750 W Min. RAM of Host System 2 64 GB 96 GB 1 The double precision performance of this GPU device is poor, thus, it can t be recommended for PIC-solver, A-Solver and I-solver (double precision) simulations. 2 The host system requires approximately 4 times as much memory as is available on the GPU cards. Although June 14, 2017 7

NVIDIA Tesla P100 Chip NVIDIA Tesla P100 PCIe 1 Min. CST version required 2017 release 2017 release Number of GPUs 1 1 Form Factor approx. 160 million mesh cells Chip Passive Cooling approx. 160 / 120 million mesh cells Dual-Slot PCI-Express Passive Cooling Memory 16 GB CoWoS HBM2 16 / 12 GB CoWoS HBM2 Bandwidth 732 GB/s 732 GB/s / 549 GB/s Single Precision Performance 2 10.6 TFlops 9.3 TFlops Double Precision Performance 2 5.3 TFlops 4.7 TFlops Power Consumption 300 W (max.) 250 W (max.) System interface NVIDIA NVLink 1x PCIe Gen 3 (x16 electrically) Power Supply of Host System min. 750 W min. 750 W Min. RAM of Host System 3 64 GB 64 GB 1 The 12 GB version has about 25 percent less performance compared to the 16 GB version. 2 Measured with BOOST enabled 3 The host system requires approximately 4 times as much memory as is available on the GPU cards. Although June 14, 2017 8

NVIDIA Quadro GP 100 (for Workstations) NVIDIA Quadro P6000 1 (for Workstations) Min. CST version required 2017 SP 2 2017 SP 2 Number of GPUs 1 1 approx. 160 million mesh cells approx. 240 million mesh cells Form Factor Dual-Slot PCI-Express Dual-Slot PCI-Express Memory 16 GB HBM2 24 GB GDDR5X Bandwidth 720 GB/s 432 GB/s Single Precision Performance 2 10.3 TFlops 12.0 TFlops Double Precision Performance 2 5.2 TFlops 0.2 TFlops Power Consumption 300 W (max.) 300 W (max.) System interface 1x PCIe Gen 3 (x16 electrically) 1x PCIe Gen 3 (x16 electrically) Power Supply of Host System min. 750 W min. 750 W Min. RAM of Host System 3 64 GB 96 GB 1 The double precision performance of this GPU device is poor, thus, it can t be recommended for PIC-solver, A-Solver and I-solver (double precision) simulations. 2 Measured with BOOST enabled 3 The host system requires approximately 4 times as much memory as is available on the GPU cards. Although June 14, 2017 9

NVIDIA Quadro M6000 1 (for Workstations) NVIDIA Quadro M6000 24 GB 1 (for Workstations) Min. CST version required 2015 SP 4 2016 SP 4 Number of GPUs 1 1 approx. 120 million mesh cells approx. 240 million mesh cells Form Factor Dual-Slot PCI-Express Dual Slot PCI-Express Memory 12 GB GDDR5 24 GB GDDR5 Bandwidth 317 GB/s 317 GB/s Single Precision Performance 6.8 TFlops 6.8 TFlops Double Precision Performance 0.2 TFlops 0.2 TFlops Power Consumption 300 W (max.) 300 W (max.) PCI Express Requirements 1x PCIe Gen 3 (x16 electrically) 1x PCIe Gen 3 (x16 electrically) Power Supply of Host System min. 750 W min. 750 W Min. RAM of Host System 2 48 GB 96 GB 1 The double precision performance of this GPU device is poor, thus, it can t be recommended for PIC-solver, A-Solver and I-solver (double precision) simulations. 2 The host system requires approximately 4 times as much memory as is available on the GPU cards. Although June 14, 2017 10