The document discusses various technological advancements, particularly in web and mobile applications, including the use of SIMDs for enhanced performance. It highlights the implementation of text recognition through video processing, applications in augmented reality, and different use cases involving Yahoo services. Additionally, it presents performance benchmarks comparing traditional JavaScript with SIMD.js for computational tasks.

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45. DeviceIndexedDB
USB File Reading
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59. navigator.getUserMedia(
{video:true, audio:false},
function(localMediaStream) {
var videoTracks =
localMediaStream.getVideoTracks();
var track = videoTracks[0];
var myWorker = new Worker("textRec.js");
track.addWorkerMonitor(myWorker));
myWorker.onmessage = function (oEvent) {
console.log("Worker recognized: " +
oEvent.data);
};
var
elem=document.getElementById('VIDEO');
elem.mozSrcObject = dest.stream;
elem.play();
}, null);

60. var textDetector =
WebImage.createTextDetector(img.width,
img.height)
onvideoprocess = function (event) {
var img = event.inputFrame;
// テキスト認識処理を実行
var words= textDetector.findText(img);
var recognizedText;
for (var ix=0; ix<words.length; ix++) {
recognizedText
= recognizedText + words[ix] + " ";
}
postMessage(recognizedText);
};

61. Use cases(Amazon FireFly)
In our case, we can
use Yahoo Service,
like Yahoo Movie,
Yahoo Shopping,
Yahoo Search...

62. Use cases(Text selection in Image, browser)
http://projectnaptha.com/

63. Use cases(Augmented Reality)

64. Use cases(Face in)

65. Use cases(Camera Panorama, HDR)

66. WWii SShhii

83. en now targets SIMD.JS
nerates SIMD.JS from C++ SIMD intrinsics & auto-vectorized code
Near-native SIMD.JS speedup
C++ JavaScript
1.00
2.03
7.18
8.13
0
2
4
6
8
10
Speedup over Scalar JS
Scalar JS Scalar C++
SIMD JS SIMD C++
on, Multiple Data
t performance & power efficiency
Cx
Cy
Cz
Cw
Ax
Ay
Az
Aw
Bx
By
Bz
Bw
+ =
SIMD Operation of
Vector Length 4
Intel® Architecture currently has SIMD
operations of vector length 4, 8, 16

85.
11
SIMD – Single Instruction, Multiple Data
SIMD operations deliver great performance & power efficiency
Scalar Operation
Cx
Cy
Cz
Cw
=
=
=
=
Ax
Ay
Az
Aw
Bx
By
Bz
Bw
+
+
+
+
Cx
Cy
Cz
Cw
Ax
Ay
Az
Aw
Bx
By
Bz
Bw
+ =
SIMD Operation of
Vector Length 4
Intel® Architecture currently has SIMD
operations of vector length 4, 8, 16

86.
13
SIMD.JS – The API
† Initial support for float32x4 and int32x4
Our SIMD prototype delivers 3x~4x Mandelbrot speedup†
Our Firefox* Prototype

87.
15
SIMD Speedups on our Chromium* Prototype
3.2
3.6 3.8 3.9
4.6
5.0
6.0
9.5
3.2
3.8
3.4
6.1
6.5
5.0
5.6
11.8
6.8
3.1
2.7
4.5 4.2
3.8
5.4
9.3
0
2
4
6
8
10
12
14
Transpose4x4 AOBench Mandelbrot MatrixMultiplication VertexTransform Average ShiftRows Matrix4x4Inverse
SIMD x-times faster than non-SIMD
3rd Generation Intel® Core™ i7 processor (3667U)@ 2.00 GHz, 32-bit, Ubuntu* 13
3rd Generation Intel® Core™ i7 processor (3667U)@ 2.00 GHz, 64-bit, Ubuntu* 13
Intel® Atom™ processor Z3770 @ 1.46GHz, Android* 4.4
Excellent early results while still focused on functionality
Theoretical speedup limit is 4
SIMD.JS benchmarks: https://github.com/johnmccutchan/ecmascript_simd/tree/master/src/benchmarks

88.
17
Emscripten now targets SIMD.JS
Emscripten generates SIMD.JS from C++ SIMD intrinsics & auto-vectorized code
Near-native SIMD.JS speedup
C/C++ JavaScript
1.00
2.03
7.18
8.13
0
2
4
6
8
10
Speedup over Scalar JS
Scalar JS Scalar C++
SIMD JS SIMD C++

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92. WEB OF THINGS

93. !!