With practical advice and a broad sampling of important algorithms, Inner Loops shows how to design programs that extend the edge of the envelope of PC performance. It provides a thorough review of 32-bit code optimization for the 486, Pentium and Pentium Pro, as well as design tips for writing fast 32-bit software.

Includes coverage of Pentium II - referred to in the chapters on Pentium Pro and MMX. No speed limits have been posted on the PC performance track, yet much software runs in the slow lane, functioning at 10 to 50 percent of its potential speed. The cause of these slowdowns? Bottlenecking on time-critical inner loops.

Inner Loops: A Sourcebook for Fast 32-bit Software Development gives the green light to optimal PC performance with practical advice and a strategic sampling of important algorithms. Focused directly on the 32-bit future of PC computing, Inner Loops explores the new rules and opportunities of a wide-open memory space, parallel instruction execution, and clock speeds in the hundreds of megahertz. You'll be taken through:

• a thorough review of 32-bit code optimization for the 486, Pentium, and Pentium Pro
• making the transition from 16-bit to 32-bit assembly language
• principles of C and assembly language optimization
• tips for fast 32-bit software design
• real-world examples of top-speed inner loops for several important PC algorithms
• what MMX, the Intel multimedia extensions, mean for speed

Author Rick Booth backs up his theory of speed with practical examples and source code, including such topics as:

• Fast memory moves
• Random numbers
• Hashing
• Huffman compression
• Sorting
• Matrix math
• JPEG's inner loop

Many chapters contain high-performance demos, which are also found on the CD. These include one of the fastest sort engines possible, a top-speed Huffman compression system, and JPEG's decompression inner loop tuned for top performance.

Consultant and developer Rick Booth is a 17-year veteran of the video game and digital video industries.

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The PC is capable of much faster performance than many people realize, but it is not unusual to find professionally-made software running inefficiently. At the crux of this problem are inner loops of code that can determine how fast a program runs. This text examines inner loops.