High-Performance and Parallel Computing with R by Dirk Eddelbuettel.
From the webpage:
This CRAN task view contains a list of packages, grouped by topic, that are useful for high-performance computing (HPC) with R. In this context, we are defining ‘high-performance computing’ rather loosely as just about anything related to pushing R a little further: using compiled code, parallel computing (in both explicit and implicit modes), working with large objects as well as profiling.
Here you will find R packages for:
- Explicit parallelism
- Implicit parallelism
- Grid computing
- Hadoop
- Random numbers
- Resource managers and batch schedulers
- Applications
- GPUs
- Large memory and out-of-memory data
- Easier interfaces for Compiled code
- Profiling tools
Despite HPC advances over the last decade, semantics remain an unsolved problem.
Perhaps raw computational capacity isn’t the key to semantics.
If not, some different approach awaits to be discovered.
I first saw this in a tweet by One R Tip a Day.