NVIDIA Jetson Xavier - Volta GPU

NVIDIA®Jetson Xavier™
Introduction
SoM Overview Carrier Boards NVIDIA Xavier Developer Kit Connect Tech Rogue Connect Tech Mimic Software Support NVIDIA JetPack
JetPack 5.0.2
Getting Started Installing JetPack Flashing the board with GUI installer JetPack Components Compiling Source Code Flashing the Board from Cmdline Performance Tuning Evaluating Performance Set Values Manually Tuning Power Maximizing Performance
Development in the Board
Getting into the Board Using Serial Console Using SSH Using Ubuntu Login Installing Packages
Video Capture and Display
Description Supported Cameras Imx219 Driver Software Support Using GStreamer Using Libargus
Processors
HD Audio and Video Subystem Video Encoder Video Decoder JPEG Encoder and Decoder Video Image Compositor Audio Processing Engine Deep Learning Accelerator Volta GPU Description Using CUDA Using OpenGL
Interfaces
I2C SD/eMMC Controller USB Controller
GStreamer Pipelines
Capture and Display H264 H265 VP9 MPEG4 Simultaneous Streams Compositor
Deep Learning
TensorRT Using TensorRT integrated with Tensorflow Parsing a Tensorflow model for TensorRT Parsing Caffe model for TensorRT Building TensorRT API examples Deep Learning Accelerator Software Support Deep Learning Tutorials Jetson Inference Jetson Reinforcement
RidgeRun Products
GstPTZR GstCUDA GstColorTransfer GstWebRTC GstRtspSink GstInterpipe GstInference GStreamer Daemon GstShark
Reference Documentation
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The Volta GPU is an architecture that powers NVIDIA high-performance computing. In this section, you will learn more about this architecture and its features. You will learn about software available to work with the Volta GPU.

• Description section is a simple description of the Volta GPU.
• CUDA section explain the samples of CUDA.
• OPENGL section explains a HelloWorld with OpenGL.

Device Capabilities

Capability	Value
CUDA Driver Version / Runtime Version	10.0 / 10.0
CUDA Capability Major/Minor version number	7.2
Total amount of global memory	15819 MBytes (16587702272 bytes)
( 8) Multiprocessors, ( 64) CUDA Cores/MP	512 CUDA Cores
GPU Max Clock rate	1500 MHz (1.50 GHz)
Memory Clock rate	1500 Mhz
Memory Bus Width	256-bit
L2 Cache Size	524288 bytes
Maximum Texture Dimension Size (x,y,z)	1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384)
Maximum Layered 1D Texture Size, (num) layers	1D=(32768), 2048 layers
Maximum Layered 2D Texture Size, (num) layers	2D=(32768, 32768), 2048 layers
Total amount of constant memory	65536 bytes
Total amount of shared memory per block	49152 bytes
Total number of registers available per block	65536
Warp size	32
Maximum number of threads per multiprocessor	2048
Maximum number of threads per block	1024
Max dimension size of a thread block (x,y,z)	(1024, 1024, 64)
Max dimension size of a grid size (x,y,z)	(2147483647, 65535, 65535)
Max dimension size of a grid size (x,y,z)	(2147483647, 65535, 65535)
Maximum memory pitch	2147483647 bytes
Texture alignment	512 bytes
Concurrent copy and kernel execution	Yes with 1 copy engine(s)
Run time limit on kernels	No
Integrated GPU sharing Host Memory	Yes
Support host page-locked memory mapping	Yes
Alignment requirement for Surfaces	Yes
Device has ECC support	Disabled
Device supports Unified Addressing (UVA)	Yes
Device supports Compute Preemption	Yes
Supports Cooperative Kernel Launch	Yes
Supports MultiDevice Co-op Kernel Launch	Yes
Device PCI Domain ID / Bus ID / location ID	0 / 0 / 0
Compute Mode	Default (multiple host threads can use ::cudaSetDevice() with device simultaneously)
CUDA Driver	CUDART

Build Device Query Tool

We obtained the properties of the CUDA devices present in the system using the deviceQuery example. In order to run it follow these steps:

1. Go to the sample's directory

cd /usr/local/cuda/samples/1_Utilities/deviceQuery

2. Construct the sample using the makefile

sudo make

3. Run the Binary

./deviceQuery