Table Of Contents
RPerl Compiler
CPerl Interpreter
Big Data
Multi-Core Computers
Events: Speed Competitions


Running Perl. Faster.

  • RPerl is the Perl compiler.
  • Low-magic Perl code is compiled into high-speed C++ code.
  • The resulting output is a binary executable file.
  • For serial apps, RPerl is at least equal in speed to C & C++.
  • For parallel apps, RPerl is auto-parallelized for even greater speed.
  • All new Perl apps must be compiled for speed & commercial success.
  • RPerl is a key component of the Perl Community Roadmap projects.
  • The goal is to compile Perl to run faster than any other language.


Corporate Perl

  • CPerl is a fork of the Perl interpreter.
  • High-magic Perl code is interpreted & executed as usual.
  • CPerl can generate bytecode for faster startup of Perl apps.
  • For some Perl apps, CPerl may also provide faster run time.
  • CPerl already supports many popular CPAN distributions.
  • The goal is to enable faster startup time than normal interpreted Perl.


Data Streams, Databases, Raw Data

  • Big data is more than just a buzz-word like "cloud" or "container".
  • By analyzing extremely large data sets, we can learn & discover:
    • Hidden Patterns
    • Future Trends
    • Previously-Unknown Correlations
  • The many potential uses of big data analytics include:
    • Human Behavior Studies
    • Consumer Product Improvement
    • Fighting Crime & Fraud
    • Disease Prevention
    • Business Systems Optimization
    • Internet of Things
  • The goal is to enable high-performance data processing for Perl.


Consumer Grade Parallelism

  • For over a decade, all new computers have a parallel multi-core CPU.
  • Existing software is built for serial execution only.
  • Software for multi-core CPUs must be built for parallel execution.
  • Perl apps can be auto-parallelized by the RPerl compiler.
  • Among the numerous consumer advantages of multi-core CPUs are:
    • Realistic Video Games
    • Desktop Scientific Computing
    • Personal Server Apps
    • Interactive Video Editing
    • Real-Time Video Compression
    • 3-D User Interfaces
  • The goal is to fully utilize multi-core CPUs for parallel Perl.


Industrial Strength Parallelism

  • For decades, all supercomputers have had parallel hardware.
  • Supercomputer apps are manually parallelized, very difficult & costly.
  • Perl apps can be auto-parallelized by the RPerl compiler.
  • Among the numerous industrial advantages of supercomputers are:
    • Shared Virtual Reality
    • Global Scientific Computing
    • Massive Server Apps
    • Feature Film Special Effects
    • Real-Time Big Data Analysis
    • Grand Challenge Solutions
  • The goal is to fully utilize supercomputers for parallel Perl.


Friendly Contests

  • Speed competitions are public games, when a group of programmers gather to compare software speed and see who is the fastest.
  • Like hackathons, speed competitions are community-driven events.
  • Each speed competition should get new apps running faster with Perl.
  • Perl Monger groups must organize fun events with a unique character:
    • Drinks & Food
    • Good Power & Wifi
    • Team Spirit
    • Friendly Rivalries
    • Local Tournaments
    • International Championship
    • Trophies & Awards
    • Bragging Rights
  • One of the benefits is to showcase high-performance code in Perl.
  • The goal is to organize annual speed competitions in every major city.