Revision as of 12:39, 2 September 2018

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Xavier
General Info
Designer	Nvidia
Manufacturer	TSMC
Model Number	Tegra194
Market	Artificial Intelligence, Embedded
Introduction	January 8, 2018 (announced) June, 2018 (launched)
General Specs
Family	Tegra
Microarchitecture
ISA	ARMv8 (ARM)
Microarchitecture	Carmel, Volta
Process	12 nm
Transistors	9,000,000,000
Technology	CMOS
Die	350 mm²
Word Size	64 bit
Cores	8
Threads	8
Electrical
TDP	30 W
TDP (Typical)	20 W

Tegra Xavier is a 64-bit ARM high-performance system on a chip for autonomous machines designed by Nvidia and introduced in 2018. Xavier is incorporated into a number of Nvidia's computers including the Jetson Xavier, Drive Xavier, and the Drive Pegasus.

Overview

Overview (HC 30)

Xavier is an autonomous machine process designed by Nvidia and introduced at CES 2018. Silicon came back in the last week of December 2017 with sampling started in the first quarter of 2018. NVIDIA plans on mass production by the end of the year. NVIDIA reported that the product is a result of $2 billion R&D and 8,000 engineering years. The chip is said to have full redundancy and diversity in its functional blocks.

The design targets and architecture started back in 2014. The chip itself comprises an eight-core CPU cluster, GPU, deep learning accelerator, vision accelerator, ISP, and a set of multimedia accelerators. Xavier features a large set of I/O and has been designed for safety and reliability supporting various standards such as Functional safety ISO-26262 and ASIL level C. The CPU cluster is fully cache coherent and the coherency is extended to all the other accelerators on-chip.

Architecture

CPU

Main article: Carmel core

The chip features eight Carmel cores, Nvidia's own custom 64-bit ARM cores.

GPU

Main article: Volta

The chip incorporates a Volta GPU with 512 CUDA Cores capable of operating in 64-bit and 32-bit floating point as well as 8-bit integer. This allows the various deep learning artificial neural networks types to run efficiently in the format most suitable for them. This translates to 1.3 CUDA TOPS (32-bit FP) and another 20 Tensor Core TOPS (16-bit FP).

Accelerators

Xavier incorporates a Programmable Vision Accelerator (PVA) for processing computer vision. It is capable of 1.6 TOPS and the ability to do stereo disparity (e.g., processing parallax between two cameras to obtain useful information such as depth), optical flow (e.g., direction and speed of vectors), and image processing. Additionally, since the chip is expected to be connected to a network of cameras (e.g., side, front, inside), the chip is capable of doing real-time encoding for all camera in high dynamic range.

The chip has an ISP with native full-range HDR support and tile rendering capable of processing at 1.5 GPIX/s.

Deep Learning Accelerator

The chip incorporates a deep learning accelerator (DLA) that implements a number of specific set of deep learning functions common to many applications. This allows them to read the highest possible energy efficiency for those operations. The DLA has a peak performance of 5 TOPS for 16-bit integers or 10 TOPS for 8-bit integer.

Memory controller

[Edit/Modify Memory Info]

	Integrated Memory Controller
	Max Type LPDDR4X-4266 Supports ECC Yes Channels 8 Width 32 bit Max Bandwidth 127.1 GiB/s 130,150.4 MiB/s 136.473 GB/s 136,472.586 MB/s 0.124 TiB/s 0.136 TB/s

I/O

• 16 CSI channels
  • 109 Gbps total bandwidth
• 1x gE interface
• 1x 10gE interface

Die

SoC

• 9,000,000,000 transistors
• 350 mm² die size
• TSMC's 12FFN

GPU

• ~89.2 mm² silicon area

CPU

See Carmel § CPU Complex.

PVA

MM Engine / DLA

• ~21.75 mm² silicon area

Documents

• CES 2018: Nvidia Drive Xavier

Bibliography

• IEEE Hot Chips 30 Symposium (HCS) 2018.