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标签:开发商: Intel Software
产品类型:控件
产品功能:测试分析
平台语言:其他|.NET|JAVA|C++/ MFC
开源水平:不提供源码
本产品的分类与介绍仅供参考,具体以商家网站介绍为准,如有疑问请来电 023-68661681 咨询。
使用“英特尔集成性能原件(英特尔 IPP)Windows 版”,可构建随选即用的功能并提高应用程序性能。它利用跨多个平台的函数库,这些函数库中的函数均针对英特尔酷睿双核处理器的多核心功能进行过优化。您还可以使用各种预先构建的函数与编解码器,涉及领域包括:音频、视频及图像处理;密码技术;语音识别;以及矩阵、矢量数学及信号处理。
Intel® Integrated Performance Primitives (Intel® IPP) is an extensive library of multicore-ready, highly optimized software functions for multimedia data processing, and communications applications.Intel IPP is one of the Intel® Performance Libraries, which provide optimizing software building blocks to complement Intel’s optimizing compilers and performance optimization tools. Intel IPP is available as a component of the Intel® Compiler Professional Editions and Compiler Suite Editions for a more complete and cost-effective solution or as a standalone product.
* 关于本产品的分类与介绍仅供参考,精准产品资料以官网介绍为准,如需购买请先行测试。
Intel IPP is validated for use with multiple generations of Intel and compatible AMD* processors, and is backed by world-class support through the Intel® Premier Support program, and by developer community forums.
Features
Multicore Processor Support
Intel IPP 6.0 fully supports today’s multicore computing platforms:
To learn more about threading and Intel IPP functions visit our threading Frequently Asked Questions (FAQ) page.
Performance-Optimized Functions
Intel IPP functions are designed to deliver performance beyond what optimized compilers alone can deliver by matching the function algorithms to low-level optimizations based on the processor’s available features such as Streaming SIMD Extensions (SSE, SSE2, SSE3, SSSE3, SSE4, and SSE4.1) and other optimized instruction sets.
Video Coding: Key algorithmic components for DV25/50/100, MPEG-2, MPEG-4, H.263, and MPEG-4 Part 10 (H.264) codecs. Figure 3 shows where Intel IPP video coding components (represented by the blue boxes) fit into the H.264 codec process flow. Functions include:
Image and 2D Signal Processing: Intel IPP is the premier library of image and 2D signal processing algorithms, and includes a rich selection of algorithms operating on images and regions within images (ROIs):
Transforms: Wavelet Fourier (FFT/DFT, real/complex) Windowing (Hamming, Bartlett) Discrete Cosine (DCT) Filtering Functions: General linear filtering Convolution/Deconvolution (LR and FFT) Box, Min, Max, Median Wiener Filters Fixed Filters (Prewitt, Sobel, Laplace, Gauss, Scharr, Roberts) Sharpening/Hipass/Lowpass Filters Geometric Transforms: Resize, Mirror, Rotate, Shear Affine transforms Perspective transformations Bilinear warping Coordinate remapping |
Image Statistics: |
Computer Vision: Intel IPP includes optimized functions for many key computer-vision operations, for applications in security, machine control, media management, media annotation and more:
Feature Detection (Corner, Canny Edge Detection) Distance Transforms Image Gradients Flood Filling Motion Templates generation Optical Flow calculation (Lucas-Kanade) |
Pattern Recognition (Haar classifiers) |
Intel IPP based optimization is automatically included in the popular OpenCV open-source computer-vision library, for enhanced performance on real-time tasks, and Intel IPP was a key software component in the winner of the 2005 DARPA Grand Challenge.
Color Conversion: Today’s explosion of digital media in multiple formats brings the need to convert digital media among different color representations. Intel IPP provides a rich set of optimized color-conversion routines on 32/24/16-bit-per-pixel formats:
Color Model Conversion: RGB, YUV, YCbCr, BGR, CbYCr, HSV, LUV, Lab, YCC, HLS, SBGR, YCoCg, YCCK, XYZ, CMYK Color Format Conversions: YCbCr422, YCbCr420, YCbCr411, CbYCr422, BGR565, BGR555, BGR565Dither |
Lookup Table Conversions (Linear/Cublic/Palette) |
[SPAN]
String Processing: Build optimized text database management, search and retrieval, or document indexing processing into your applications using Intel IPP’s optimized string operations.
Substring substitution/insertion String concatenation/splitting Upper/lower case conversions |
String/Substring matching |
JPEG Coding: Key algorithmic components for JPEG, JPEG 2000, and Motion JPEG codecs. Figure 4 shows where Intel IPP JPEG coding components (represented by the blue boxes) fit into the JPEG and JPEG 2000 codec process flow.
Speech Coding: Intel IPP includes a comprehensive set of routines supporting the following speech codecs/functions:
G.722.1 G.722 Sub-Band ADPCM G.723.1 G.726 G.728 Echo Cancellation |
G.729 |
The freely-downloadable Intel IPP Universal Speech Class (USC) code samples illustrate the use of the low-level Intel IPP functions to build speech codecs.
Signal Processing: Includes signal processing features for the following:
Filtering and Convolution: Finite Impulse Response (FIR) Infinite Impulse Response (IIR) Median filtering Cyclic convolution Auto/Cross-correlation Transforms: Fourier (FFT, DFT, Goertzel) Discrete Cosine Transforms (DCT) Hilbert Transforms Wavelet Transforms (fixed/custom filters) Power spectrum calculation Windowing/Sampling: Upsampling/Downsampling Windowing (Bartlett/Blackman/Hamming/Hann/Kaiser) |
Array/Signal Initialization/Manipulation: |
Data Compression: In addition to video, audio and image compression with codecs, Intel IPP provides functions for lossless compression methods, such as those used in the popular “zlib” (inflate and deflate) and “libbzip2” libraries.
Burrows-Wheeler-Transform techniques: Burrows-Wheeler Transform (BWT) Generalized Interval Transform Move-to-Front (MTF) Run-length encoding (RLE) |
Entropy coding: |
Audio Coding: Key algorithmic components for MP3,and AAC codecs. Figure 5 shows where Intel IPP JPEG coding components (represented by the blue boxes) fit into the AAC codec process flow. Functions include:
The Video and Audio code samples illustrate sample codec implementations using Intel IPP functions.[SPAN]
Speech Recognition: Build advanced speech recognition, Voice-over-IP, and voice annotation capabilities in applications, using Intel IPP’s broad range of speech-recognition capabilities:
Feature Processing Model Evaluation Model Estimation Model Adaptation Vector Quantization |
Acoustic Echo Cancellation (AEC) |
Vector/Matrix Operations: Intel IPP contains a rich set of matrix and vector operations for a wide variety of applications, including physics modeling and 3D transform/lighting calculations.
Matrix algebra: Eigenvalue/eigenvector calculation Least Squares (QR decompositions/back-sub) Linear Systems (LU/Cholesky) Region-of-Interest (ROI) extraction Fast copy of vectors/matrices |
Vector algebra: |
For applications requiring high-performance linear algebra operations on very large data sets, the Intel® Math Kernel Library may also be of interest.
Cryptography: Use Intel IPP to quickly build robust, high-performance cryptographic modules and applications. Below are some of the many cryptographic building blocks included in Intel IPP’s cryptography functions.
Symmetric Ciphers: Block Ciphers (AES/Rijndael, DES, Triple DES, Blowfish, Twofish) Stream Ciphers (ARCFour) One-way Hashing: Generalized Hashing (MD5, SHA1-512) Mask Generation (MD5, SHA1-512) Data Authentication: Keyed Hash (HMAC-MD5, HMAC-SHA1-512) Data Authentication Functions (DES, TDES, Rijndael, Blowfish, Twofish) |
Asymmetric Cryptography: |
Intel IPP’s cryptographic functions have been validated according to the Cryptographic Algorithm Validation Program (CAVP).
Name |
Standards/Certificate |
Discrete Logarithm (Digital Signature Standard) |
FIPS 186-2 / Cert 190 |
Integer Factoring (Digital Signature Standard) |
FIPS 186-2, ANSI X9.31-1998 / Cert 181 |
Eliptic Curve Digital Signature Algorithm (ECDSA) |
FIPS 186-2, ANSI X9.62-1998 / Cert 40 |
Random Number Generator |
FIPS 186-2 / Cert 245 |
Note: To access the Cryptography Library, you must request access from Intel.
Ray-Tracing and Rendering: Core operations used in ray-tracing, realistic image rendering, and physics applications:
Bounding-box calculations Object-ray intersections Shadow/Reflection calculations |
Data Integrity: Error correcting codes are vitally important to preserving the integrity of data in transmission, storage and encoding. For example transmission lines can be unreliable and introduce data errors, spurious signals can occur when saving data to a compact disk, and errors can occur when reading bar codes. Using error correcting codes like Reed-Solomon is a good way to correct these errors.
System Requirements
Please refer to the section below for installation requirements and system requirements that match your application’s target platform.[SPAN]
Application Target Platforms
32-bit Intel® architecture Platforms |
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64-bit Intel 64 architecture-based platforms |
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64-bit IA-64 architecture-based platforms |
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32-bit IA-32 Architecture-Based and Compatible Platforms
(Intel Core 2 processor family, Intel Core processor family, Intel Pentium processors, and compatible AMD processors)
|
OS Version |
Supported Compilers |
Microsoft Windows |
Microsoft Windows Vista* |
Intel® C++ Compiler for Windows* OS version 10.1 and 11.0 |
Linux |
Linux system with glibc 2.2.4, 2.2.5, 2.2.93, 2.3.2 or 2.3.3 and the 2.4.X or 2.6.X Linux kernel as represented by the following distributions. Note: Not all distributions listed are validated and not all distributions are listed.
|
Intel® C++ Compiler version 10.1 and 11.0 for Linux * for IA-32 architecture |
Mac OS X |
10.4.3 or later |
Intel C++ Compiler 10.1 and 11.0 for Mac OS X, including Professional Edition |
64-bit Intel 64 Architecture-Based Platforms
(Intel Core 2 processor family, Intel Pentium D processors, Intel Xeon processors, and processors from AMD compatible with Intel 64 architecture)
|
OS Version |
Supported Compilers |
Microsoft Windows |
Microsoft Windows Vista* |
Intel® C++ Compiler for Windows* OS version 10.1 and 11.0 for processors based on Intel® 64 architecture |
Linux |
Linux system with glibc 2.2.4, 2.2.5, 2.2.93, 2.3.2 or 2.3.3 and the 2.4.X or 2.6.X Linux kernel as represented by the following distributions. Note: Not all distributions listed are validated and not all distributions are listed.
|
Intel C++ Compiler 10.1 or 11.0 for Linux |
Mac OS X |
10.4.6 or later |
Intel C++ Compiler 10.1 and 11.0 for Mac OS X |
[SPAN]
64-bit IA-64 Architecture-Based Platforms
(Intel® Itanium® processors)
|
OS Version |
Supported Compilers |
Microsoft Windows |
Microsoft Windows Server 2008 |
Intel® C++ Compiler for Windows* OS version 10.1 and 11.0 for Intel Itanium Processors |
Linux |
Linux system with glibc 2.2.4, 2.2.5, 2.2.93, 2.3.2 or 2.3.3 and the 2.4.X or 2.6.X Linux kernel as represented by the following distributions. Note: Not all distributions listed are validated and not all distributions are listed.
|
Intel C++ Compiler 10.1 and 11.0 for Linux |
Intel Atom Architecture-based Platforms
|
OS Version |
Supported Compilers |
|
|
|
Linux |
Linux system with glibc 2.2.4, 2.2.5, 2.2.93, 2.3.2 or 2.3.3 and the 2.4.X or 2.6.X Linux kernel as represented by the following distributions.
|
Intel® C++ Compiler version 10.1 & 11.0 for Linux* OS for IA-32 processors |
Installation Requirements
|
Supported Software / Hardware |
Operating Systems |
Microsoft Windows:
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Processor Requirements |
IA-32 architecture-based and compatible platforms:
|
Minimum Disk Space for Install |
900 MB plus 300 MB of temporary space during installation for each Application Target Platform |
更新时间:2014-02-19 13:52:20.000 | 录入时间:2006-06-09 14:24:00.000 | 责任编辑:陈俊吉
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