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Optimizing Vertex Linear Interpolation with Intel® Pentium® III and Pentium® 4 Processors

Introduction

Increasing processor speeds have led to the introduction of more complex algorithms that provide games with a more dynamic player environment, resulting in a decline in the use of vertex linear interpolation for animations. Additionally, vertex processing in hardware is increasingly minimizing the need for software interpolation. However, most users do not have hardware vertex processors, so it's important to optimize your software interpolation to support this gaming segment.
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  • How to Vectorize Code on 32-Bit Intel® Architecture


    Challenge

    Vectorize code for greater performance. The SIMD features of Streaming SIMD Extensions (SSE), Streaming SIMD Extensions 2 (SSE2) and MMX™ technology require new methods of coding algorithms. One of them is vectorization. Vectorization is the process of transforming sequentially executing, or scalar, code into code that can execute in parallel, taking advantage of the SIMD architecture parallelism.

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  • Developing for Speed: A Four-Step Approach

    by George Walsh


    Introduction

    There's really no denying that application optimization yields performance benefits. The question in each case is whether time spent optimizing and resulting performance gains is worth the development time, effort and cost. As part of his work with the Intel® software team Eric Palmer works closely with ISVs, helping to boost performance of their applications. Palmer has developed a four-step approach--it works for him, and it will work for your applications too.

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  • Linux* on Intel® Architecture Improved Performance and TCO


    Introduction

    During the design of the Pentium® 4 processor, Intel's design-engineering team reaped the rewards of migrating from legacy RISC*-based systems to Linux* on Intel architecture.

    Design-engineering teams at Intel have achieved substantial savings in Total Cost of Ownership (TCO) by migrating to Linux on Intel® architecture from legacy UNIX* systems on RISC-based architecture. At the same time, those teams have achieved substantial productivity gains from the performance benefits associated with the migration.

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  • How to Implement the LibM Math Library


    Challenge

    Implement the LibM Math Library. The LibM library provides highly optimized scalar math functions that serve as direct replacements for the standard C calls. The LibM versions are fully accurate and do not attempt to extract algorithm-level parallelism, so they can be applied in even the most rigid coding situations.

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