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Welcome to the site for Scott Meyers’ book-in-progress, Fastware!: Straight Talk about Fast Code for quant development

(Last Updated On: January 24, 2012)

Welcome to the site for Scott Meyers’ book-in-progress, Fastware!: Straight Talk about Fast Code for quant development

So you have read (everyone in this group should have) classic Scott Meyers’ C++ books – including three acclaimed books on C++ programming – Effective C++, Effective STL, More Effective C++.

Unlike Scott’s “Effective” books, Fastware! will be language-independent, as applicable to programmers in C#, Java, Python, Ruby, etc., as to C and C++ developers.

Vision

The executive summary for Fastware! is:

A book of under 300 pages covering the most important practical information about designing and implementing programs and systems that are fast. Aimed at architects, designers, and implementers of software systems targeting any problem domain using any programming language(s). Suitable for students or professionals. Assumes software development experience, but no formal background in Computer Science. Brings together the most important speed-related information every developer should be familiar with.

http://www.aristeia.com/Fastware/

Topics aristeia.com

Welcome to the site for Scott Meyers’ book-in-progress, Fastware!: Straight Talk about Fast Code. The executive summary for Fastware! is: A book of under 300 pages covering the most important practical information about…

 

Topics

Fastware! is expected to include chapters on the following topics:

Introduction: Why fastware matters; fastware vs. “performance,” “efficiency,” “scalability,” “responsiveness,” etc.

Memory and Processors: Memory hierarchies, cache behavior, processor variations, and their implications for software developers. Specialized hardware, e.g., GPUs, FPGAs, DSPs, etc.

Collecting Empirical Data: The importance of empirical data; logging for data mining; development environments vs. deployment environments, etc.

Exploiting Constraints: General-purpose solutions vs. special-purpose solutions; the importance of verifying constraints; “cheating.”

Avoiding Computation: Precomputation (e.g., indexing, lookup tables, prefetching, etc.), caching, lazy evaluation, incremental computation, etc.

Data Structures and Algorithms: Complexity analysis and the real world; cache- and concurrency-friendliness; evaluation of standard facilities in C#, Java, and C++; important algorithms, etc.

IO: Disk IO vs. network IO; buffering; defragmentation; compression; striping; minimizing transmission distance; using deltas; memory mapping, etc.

Concurrency: Data/task/pipelining parallelism; synchronization primitives; insulation; alternative approaches (e.g., lock-free, stream processing); exploiting “extra” cores and threads.

Memory Management: For native code (C/C++); for managed code (Java/.NET); heaps/pools/arenas; working with generational and compacting collectors, etc.

Environment Issues: Your code is a minority of what executes; compilers and options; WPO and PGO; runtimes and options; getting the most out of third-party libraries and applications, etc.

Creating Fastware: Treating speed as a correctness criterion; designing for speed; assuming the existence of HW concurrency, etc.
Accelerating Slowware: Profilers and other tools; analyzing logs; “disturb and observe” strategies, etc.

 

 

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