Summary

  • Catalytic computing analyses the use of a full memory drive as a computational tool to increase a computer’s processing power.
  • It grew out of previous work analysing the resources required to solve different computing problems and sorts these into different classes.
  • This included the P and L classes, with L containing problems that can be solved with fast, memory-efficient algorithms.
  • Most researchers believe that all P problems can be solved with only a small amount of memory, leading to the question of whether this can be proved for an individual P problem, such as the ‘tree evaluation’ problem.
  • This problem involves solving a simpler maths problem that turns two input numbers into a single output, repeatedly, in layers, to find a final output.
  • Cook and McKenzie suspected that it couldn’t be solved with low memory, but feared that a way to do so might be found through the use of uncommon algorithms.
  • This sparked a quest to prove or disprove this, which led to the development of catalytic computing, surprisingly showing that full memory can be helpful in some cases.

By Ben Brubaker

Original Article