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Imagine you wrote a program for a pleasingly parallel problem, where each thread does its own independent piece of work, and the threads don’t need to coordinate except joining the results at the end. Obviously you’d expect the more cores it runs on, the faster it is. You benchmark it on a laptop first and indeed you find out it scales nearly perfectly on all of the 4 available cores. Then you run

Some programming languages like Java or Scala offer more than one way to express a concept of “lack of value”. Traditionally, a special null value is used to denote references that don’t reference any value at all. However, over time we have learned that using nulls can be very error-prone and can cause many troubles like NullPointerException errors crashing a program in the most unexpected moment

Blog on programming, optimization and performance analysis August 24, 2020 One of the well-known ways of speeding up a data processing task is partitioning the data into smaller chunks and processing the chunks in parallel. Let’s assume we can partition the task easily, or the input data is already partitioned into separate files which all reside on a single storage device. Let’s also assume the a