Summary of GRA115Q 3U VPX GPU BOARD FOR INTENSIVE RADAR AND AI APPLICATIONS
The GRA115Q 3U VPX is a high-performance GPU board based on NVIDIA Turing architecture with dedicated tensor cores for accelerated deep learning inference. It supports either Quadro RTX 5000 or RTX 3000 GPUs, offering up to 9.49 TFLOPS single-precision performance and 256-bit 16 GB GDDR6 memory with up to 448 GB/s bandwidth. Intended for radar, video analysis, situational awareness, and moving map applications, it provides multiple output configurations, broad OS and API support, DVI video output, and a PCIe interface for peripherals.
Parts used in the GRA115Q 3U VPX:
- NVIDIA Quadro RTX 5000 GPU (option)
- NVIDIA Quadro RTX 3000 GPU (option)
- 256-bit 16 GB GDDR6 graphics memory
- 3U VPX board form factor (GRA115Q)
- Dual DisplayPort 1.4a outputs
- Dual SL-DVI outputs
- Quad SL-DVI outputs (alternative configuration)
- Quad DisplayPort 1.4a outputs (alternative configuration)
- DVI video output
- Embedded PCIe interface
The GRA115Q 3U VPX is a GPU board for applications like radar and video analysis. It is a good option for systems that require high-performance graphical computations with compatible advanced GPUs. The General Purpose GPU board is based on NVIDIA Turing architecture that comes with dedicated tensor cores for accelerating deep learning inferences. Hence, it could be a good fit for use cases in situational awareness and moving map applications
GRA115Q GPU board comes with two options for GPUs; NVIDIA Quadro RTX 5000 or Quadro RTX 3000 GPU that have 4 times increased performance efficiency over the NVIDIA Pascal class GPUs. The Quadro RTX5000 offers up to 9.49 TFLOPS of single-precision floating-point compute performance. It can also accelerate up to 448 GB/s memory bandwidth with its 256-bit 16 GB GDDR6 graphics memory for high-intensity data applications.
Output Configurations For GRA115Q GPU Board
- Dual Display Port 1.4a + Dual SL-DVI outputs 2x DisplayPort 1.4a, 2x SL-DVI at 1920 x 1200 both working up to 60Hz.
- Quad SL-DVI outputs have 4x SL-DVI at 1920 x 1200 works at 60Hz outputs.
- Quad DisplayPort 1.4a at 4K functions up to a frequency of 60Hz.
The SL-DVI outputs are compatible with the GRA112D, GRA113D, GRA112Q, GRA113Q, and the GR5 3U VPX graphics boards. GRA115Q GPU board has a flexible range of operating system support including CUDA, Linux, NVIDIA CUDA, OpenCL, OpenGL, Windows 7, and Windows 10. It features a DVI (Digital Visual Interface) video output for connection to a display device and controllers. It also has an embedded PCle interface for connecting additional peripheral components.
Read more: GRA115Q 3U VPX GPU BOARD FOR INTENSIVE RADAR AND AI APPLICATIONS
- What GPUs are available for the GRA115Q 3U VPX?
The board is offered with NVIDIA Quadro RTX 5000 or Quadro RTX 3000 GPUs. - What performance does the Quadro RTX 5000 provide?
The Quadro RTX 5000 offers up to 9.49 TFLOPS of single-precision floating-point compute performance. - How much graphics memory and bandwidth does the GRA115Q support?
It uses 256-bit 16 GB GDDR6 graphics memory and can accelerate up to 448 GB/s memory bandwidth. - What display output configurations are supported?
Supported configurations include Dual DisplayPort 1.4a + Dual SL-DVI, Quad SL-DVI, and Quad DisplayPort 1.4a. - What resolutions and refresh rates do the outputs support?
SL-DVI outputs support 1920 x 1200 at 60 Hz; Quad DisplayPort 1.4a supports 4K at up to 60 Hz. - Which other VPX boards are SL-DVI outputs compatible with?
The SL-DVI outputs are compatible with GRA112D, GRA113D, GRA112Q, GRA113Q, and the GR5 3U VPX graphics boards. - What operating systems and APIs does the GRA115Q support?
It supports CUDA, Linux, NVIDIA CUDA, OpenCL, OpenGL, Windows 7, and Windows 10. - Does the GRA115Q provide a PCIe interface?
Yes, it features an embedded PCIe interface for connecting additional peripheral components. - Is the GRA115Q suitable for AI and radar applications?
Yes, it is presented as a good fit for radar, video analysis, situational awareness, and moving map applications due to its tensor cores and high performance.
