© Copyright Khronos Group 2014 - Page 1

Open API Standards for Mobile Graphics, Compute and Vision Processing

GTC, March 2014 Neil Trevett

Vice President Mobile Ecosystem, NVIDIA President Khronos

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Khronos Connects Software to Silicon

Open Consortium creating ROYALTY-FREE, OPEN STANDARD APIs for hardware acceleration

Defining the roadmap for low-level silicon interfaces needed on every platform

Graphics, compute, rich media, vision, sensor and camera

processing

Rigorous specifications AND conformance tests for cross-

vendor portability

Acceleration APIs BY the Industry

FOR the Industry

Well over a BILLION people use Khronos APIs Every Day…

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Khronos Standards

Visual Computing - 3D Graphics - Heterogeneous Parallel Computing

3D Asset Handling - 3D authoring asset interchange

- 3D asset transmission format with compression

Acceleration in HTML5 - 3D in browser – no Plug-in

- Heterogeneous computing for JavaScript

Camera Control API

Over 100 companies defining royalty-free APIs to connect software to silicon

Sensor Processing - Vision Acceleration - Camera Control - Sensor Fusion

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The OpenGL Family OpenGL 4.4 is the industry’s most advanced 3D API Cross platform – Windows, Linux, Mac, Android Foundation for productivity apps Target for AAA engines and games

The most pervasively available 3D API – 1.6 Billion devices and counting Almost every mobile and embedded device – inc. Android, iOS Bringing proven desktop functionality to mobile

JavaScript binding to OpenGL ES Enabling the Web with GPU access Almost pervasive availability on mobile and desktop browsers Truly portable 3D apps with HTML5

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OpenGL ES 3.1 Launched at GDC! • Headline features - Compute Shaders and Draw-Indirect

- Compute shaders can create geometry or other rendering data

• Expecting rapid adoption - driver upgrade for many SOCs - Backward compatible with 2.0/3.0 so apps can incrementally adopt features

• Enabling desktop OpenGL to be used for mobile development - ARB_ES_3_1_compatibility specification to support “OpenGL ES 3.1 context”

2002 Working Group

Formed

2003 1.0

2004 1.1

2007 2.0

2012 3.0

2014 3.1

Driver Update

Silicon Update

Silicon Update

Driver Update

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OpenGL Fallacy: Old and Inefficient

Immediate Mode Fixed

Function

Ancient crufty stuff

Feedback

Selection

Evaluators

Display Lists

Selectors

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OpenGL Reality: Modern & Efficient

Bindless ARB

SSBO GL4.3

Multi-Draw Indirect GL4.3

UBO GL3.1

Texture Arrays GL3.0

Buffer Storage GL4.4

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indirect draw

buffer object

buffer object

texture object

buffer object

buffer object

texture object

buffer object

buffer object

buffer object

render target

buffer object

Classic OpenGL Model

CPU

GPU

…

…

Memory

cmd

cmd

cmd

cmd

Direct Drawing Commands (via the command fifo)

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indirect draw

buffer object

indirect draw

buffer object

texture object

buffer object

indirect draw

buffer object

texture object

buffer object

buffer object

buffer object

render target

buffer object

Efficient OpenGL Model

CPU

CPU

CPU

CPU

GPU …

…

Memory

CPU Writes Memory – multi-threaded (no API)!

GPU Writes Commands to Memory Reads Commands from Memory

No API – Minimal CPU Involvement

Memory access mediated through

OpenGL fences

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Results • OpenGL enables scalable multi-threading with no new API

- CPU and GPU Cores just write to memory - GPU work creation - builds buffers, constructs MDI commands

• Integer multiple speedups ~5x – ~15x (not a typo) - On driver limited cases, obviously

• Works TODAY on existing drivers! - Mostly OpenGL 4.2+ - Extensions are at least EXT

• Does not require a new object model - Does not require breaking existing applications

• http://blogs.nvidia.com/blog/2014/03/20/opengl-gdc2014/

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EGL 1.5 Released • EGL 1.5 brings functionality from multiple

extensions into core - Increased reliability and portability

• EGLImages - Sharing textures and renderbuffers

• Context Robustness - Defending against malicious code

• EGLSync objects - Improved OpenGL /OpenCL interop

• Platform extensions - Standardized interactions for multiple OS

e.g. Android and 64-bit platforms

• sRGB colorspace rendering

• NEXT – EGLStreams into core for vision and camera interop

Applications

OS and Display Platforms

Application Portability EGL abstracts graphics context

management, surface and buffer binding and rendering

synchronization

API Interop EGL provides efficient

transfer of data and events between Khronos APIs

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OpenCL as Parallel Compute Foundation • 100+ tool chains and languages leveraging OpenCL

- Heterogeneous solutions emerging for the most popular programming languages

JavaScript binding to OpenCL

WebCL River Trail Language

extensions to JavaScript

C++ AMP Shevlin Park Uses Clang and LLVM

OpenCL provides vendor optimized, cross-platform, cross-vendor access to

heterogeneous compute resources

Harlan High level

language for GPU programming

Compiler directives for

Fortran C and C++

Aparapi Java language extensions for

parallelism

PyOpenCL Python wrapper

around OpenCL

Image Processing Language

Halide

Device X Device Y Device Z

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Widening OpenCL Ecosystem

Device X Device Y Device Z

OpenCL C Kernel Source

SPIR Generator (e.g. patched Clang)

Alternative Language for

Kernels

Alternative Language for

Kernels

Alternative Language for

Kernels

High-level Frameworks

High-level Frameworks Apps and

Frameworks

OpenCL C Runtime

OpenCL run-time can consume SPIR

SPIR Standard Portable

Intermediate Representation SPIR 1.2 Released

January 2014

SYCL Programming abstraction that combines

portability and efficiency of OpenCL with ease of use and flexibility of C++

SPIR 1.2 Released here at GDC!

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WebCL: Heterogeneous Computing for the Web • WebCL 1.0 specification officially finalized today at GDC!

- https://www.khronos.org/webcl

• WebCL defines JavaScript binding to the OpenCL APIs - Enables initiation of Kernels written in OpenCL C within the browser

• Typical Use Cases - 3D asset codecs, video codecs and processing, imaging and vision processing - Physics for WebGL games, Online data visualization, Augmented Reality

OpenCL Kernel Code

OpenCL Kernel Code

OpenCL Kernel Code

OpenCL C Kernel Code

GPU

DSP CPU

CPU HW

JavaScript Platform API To query, select and initialize

compute devices

JavaScript Runtime API To build and execute kernels

across multiple devices

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Content JavaScript, HTML, CSS, ...

WebGL/WebCL Ecosystem

JavaScript Middleware

JavaScript HTML5 / CSS

Browser provides WebGL and WebCL Alongside other HTML5 technologies

No plug-in required

OS Provided Drivers WebGL uses OpenGL ES 2.0 or

Angle for OpenGL ES 2.0 over DX9 WebCL uses OpenCL 1.X

Content downloaded from the Web

Middleware can make WebGL and WebCL accessible to non-expert programmers

E.g. three.js library: http://threejs.org/ used by majority of WebGL content

Low-level APIs provide a powerful foundation for a rich JavaScript

middleware ecosystem

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OpenVX – Power Efficient Vision Acceleration • Acceleration API for real-time vision

- Focus on mobile and embedded systems

• Enable diverse efficient implementations - From CPUs, through GPUs and DSPs

to dedicated hardware

• Foundational API for vision acceleration - Can be used by middleware libraries or

by applications directly

• Complementary to OpenCV - Which is great for prototyping

• Khronos open source sample implementation - To be released with final specification - Sample - not reference - spec remains the

definitive definition of OpenVX operation Open source sample

implementation Hardware vendor implementations

OpenCV open source library

Other higher-level CV libraries

Application

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OpenVX Graphs – The Key to Efficiency • Vision processing directed graphs for power and performance efficiency

- Each Node can be implemented in software or accelerated hardware - Nodes may be fused by the implementation to eliminate memory transfers - Processing can be tiled to keep data entirely in local memory/cache

• EGLStreams can provide data and event interop with other Khronos APIs - BUT use of other Khronos APIs are not mandated

OpenVX Node

OpenVX Node

OpenVX Node

OpenVX Node

Heterogeneous Processing

Native Camera Control

Example OpenVX Graph

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OpenVX 1.0 Function Overview • Core data structures

- Images and Image Pyramids - Processing Graphs, Kernels, Parameters

• Image Processing - Arithmetic, Logical, and statistical operations - Multichannel Color and BitDepth Extraction and Conversion - 2D Filtering and Morphological operations - Image Resizing and Warping

• Core Computer Vision - Pyramid computation - Integral Image computation

• Feature Extraction and Tracking - Histogram Computation and Equalization - Canny Edge Detection - Harris and FAST Corner detection - Sparse Optical Flow

OpenVX 1.0 defines framework for

creating, managing and executing graphs

Focused set of widely used functions that are

readily accelerated

Implementers can add functions as extensions

Widely used extensions adopted into future versions of the core

OpenVX Specification Evolution

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OpenVX and OpenCV are Complementary

Governance Community driven open source with no formal specification

Formal specification defined and implemented by hardware vendors

Conformance No conformance tests for consistency and every vendor implements different subset

Full conformance test suite / process creates a reliable acceleration platform

Portability APIs can vary depending on processor Hardware abstracted for portability

Scope Very wide

1000s of imaging and vision functions Multiple camera APIs/interfaces

Tight focus on hardware accelerated functions for mobile vision Use external camera API

Efficiency Memory-based architecture Each operation reads and writes memory

Graph-based execution Optimizable computation, data transfer

Use Case Rapid experimentation Production development & deployment

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Vision Developers – API Choice

Out of the Box Vision Framework Vision operators and graph framework library Can run on dedicated hardware – no compiler Suited for low-power, always-on acceleration

Easier performance portability to diverse hardware

GPU Compute Shaders Flexible GLSL compute and imaging Easy to integrate into existing graphics apps Can mean less APIs and contexts for app to manage Limited to single GPU

General Purpose Heterogeneous Programming Framework Flexible, low-level access to any devices with OpenCL compiler Single run-time framework for CPUs, GPUs, DSPs, hardware Needs full compiler stack and IEEE precision Can be used to code new OpenVX nodes

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Need for Camera Control API • Advanced control of ISP and camera subsystem

- Generate sophisticated image stream for advanced imaging & vision apps

• No platform API currently fulfills all developer requirements - Portable access to growing sensor diversity: e.g. depth sensors and sensor arrays - Cross sensor synch: e.g. synch of camera and MEMS sensors - Advanced, high-frequency per-frame burst control of camera/sensor: e.g. ROI - Multiple input, output re-circulating streams with RAW, Bayer or YUV Processing

Pre-processing Image Signal Processor (ISP) Post-processing

Sensor, Color Filter Array Lens, Flash, Focus, Aperture

Bayer RGB/YUV Image/Vision Applications

Lens, sensor, aperture control 3A - Auto Exposure (AE), Auto White Balance (AWB), Auto Focus (AF)

Scope of Camera Control API

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Camera API Architecture will be FCAM-based • No global state

- State travels with image requests - Every stage in the pipeline may have different state - Enables fast, deterministic state changes

• Synchronize devices - Lens, flash, sound capture, gyro… - Devices can schedule Actions - E.g. to be triggered on exposure change

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Low-level Sensor Abstraction API

Apps Need Sophisticated Access to Sensor Data Without coding to specific

sensor hardware

Apps request semantic sensor information StreamInput defines possible requests, e.g.

Read Physical or Virtual Sensors e.g. “Game Quaternion” Context detection e.g. “Am I in an elevator?”

StreamInput processing graph provides optimized sensor data stream

High-value, smart sensor fusion middleware can connect to apps in a portable way

Apps can gain ‘magical’ situational awareness

Advanced Sensors Everywhere Multi-axis motion/position, quaternions,

context-awareness, gestures, activity monitoring, health and environmental sensors Sensor Discoverability

Sensor Code Portability

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Khronos APIs for Augmented Reality

Advanced Camera Control and stream

generation

3D Rendering and Video Composition

On GPU

Audio Rendering

Application on CPUs, GPUs

and DSPs

Sensor Fusion

Vision Processing

MEMS Sensors

Camera Control API

EGLStream - stream data

between APIs

Precision timestamps on all sensor samples

AR needs not just advanced sensor processing, vision acceleration, computation and rendering - but also for

all these subsystems to work efficiently together

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NVIDIA Use of Khronos Standards • Shipping

- OpenGL 4.4 - OpenGL ES 3.X - WebGL 1.0 - OpenCL 1.X - EGL 1.4

• Implementing - OpenVX 1.0 Provisional

(foundational framework for VisionWorks)

• Participating - Camera Working Group - StreamInput

Camera Control API