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Article

Being Successful with the Intel® Compilers -- You Need to Know

Tips and techniques on using the Intel® Compilers to maximize your application performance.
Автор: Последнее обновление: 05.03.2019 - 22:07
Article

How to Vectorize Code Using Intrinsics on 32-Bit Intel® Architecture

Challenge
Автор: админ Последнее обновление: 15.12.2017 - 17:08
Article

How to Manipulate Data Structure to Optimize Memory Use on 32-Bit Intel® Architecture

Demonstrates how a Structure of Arrays organization of data makes it easier to get a performance benefit from SIMD
Автор: админ Последнее обновление: 05.02.2019 - 10:23
Article

Intel® Software Development Emulator Download

Download page for the latest Intel® Software Development Emulator
Автор: Ady Tal (Intel) Последнее обновление: 03.07.2019 - 20:00
Article

Floating-Point Performance and Vectorization

Challenge
Автор: админ Последнее обновление: 07.06.2017 - 12:17
Article

Intel® IPP Memory Function ippMalloc/Free FAQ

Information about Intel® Integrated Performance Primitives (Intel® IPP) memory functions
Автор: Последнее обновление: 31.07.2019 - 14:30
Article

Intel® MKL and Intel® IPP: Choosing a High Performance FFT

The purpose of this document is to help developers determine which FFT, Intel® MKL or Intel® IPP is best suited for their application.
Автор: Последнее обновление: 31.07.2019 - 14:23
Article

Requirements for Vectorizable Loops

Vectorization is one of many optimizations that are enabled by default in the latest Intel compilers. In order to be vectorized, loops must obey certain conditions, listed below. Some additional ways to help the compiler to vectorize loops are described.
Автор: Martyn Corden (Intel) Последнее обновление: 27.03.2019 - 14:36
Article

OpenMP* and the Intel® IPP Library

How to configure OpenMP in the Intel IPP library to maximize multi-threaded performance of the Intel IPP primitives.
Автор: Последнее обновление: 31.07.2019 - 14:30
Article

IIR Gaussian Blur Filter Implementation using Intel® Advanced Vector Extensions

This white paper proposes an implementation for the Infinite Impulse Response (IIR) Gaussian blur filter using Intel® Advanced Vector Extensions (Intel® AVX) instructions. For a 2048x2048 image size, the AVX implementation is ~2X faster than the SSE code.
Автор: Brijender Bharti (Intel) Последнее обновление: 07.06.2017 - 12:19