Big projects require lots of cycles.
You can achieve more computational efficiency and throughput via parallelism:
- Computers are fast at doing something once or a couple of times, not so fast if they have to do it millions of times,
- Processing a little bit of data happens quickly. Processing gigabytes of data can take awhile.
SMPs with SIMD are cheap and readily availableMulti-core CPUs (symmetric multi-processing - SMP; single instruction stream, multiple data stream - SIMD) solve the heat problem that dooms faster, more complex single core machines. The trick is to use them more intelligently and effectively.
Examples of some applications that can benefit from medium grain parallelism:
- Array slices and data parallel operations on (sub)arrays
- Processing multiple files
- Graphical Rendering
- Pattern detection
- Processing tree data structures and rewriting them
- Data attribute evaluation
- Transaction processing
We have expertise in constructing parallel programs. Our DMS platform can perform analysis and transformations on your code. We'd be happy to consult with you. Drop us a line at email@example.com