Web of Technologies
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Transcript of Web of Technologies
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WEB MOBILE FIREFOX OS
29 ヶ国
15 キャリア
WEB OF THINGS
O S W F
I
L E B T
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wonderstruck
So, the Project FoxEye came to the world.
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);
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); };
Use cases(Amazon FireFly)In our case, we can use Yahoo Service, like Yahoo Movie, Yahoo Shopping, Yahoo Search...
Use cases(Text selection in Image, browser)
http://projectnaptha.com/
Use cases(Augmented Reality)
Use cases(Face in)
Use cases(Camera Panorama, HDR)
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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
1.002.03
7.188.13
02468
10
Speedup over Scalar JS
Scalar JS Scalar C++
SIMD JS SIMD C++
11
SIMD – Single Instruction, Multiple Data
SIMD operations deliver great performance & power efficiency
Scalar Operation
Cx
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+
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Cx
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SIMD Operation of Vector Length 4
Intel® Architecture currently has SIMD operations of vector length 4, 8, 16
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
13
SIMD.JS – The API
† Initial support for float32x4 and int32x4
Our SIMD prototype delivers 3x~4x Mandelbrot speedup†
Our Firefox* Prototype
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SIMD Speedups on our Chromium* Prototype
3.2 3.6 3.8 3.94.6
5.0
6.0
9.5
3.23.8
3.4
6.16.5
5.05.6
11.8
6.8
3.12.7
4.5 4.2 3.8
5.4
9.3
0
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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* 133rd 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
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
1.002.03
7.188.13
02468
10
Speedup over Scalar JS
Scalar JS Scalar C++
SIMD JS SIMD C++
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WEB OF THINGS
!!