In this talk I will explore best practices when accessing data on local or shared file systems. Examples of what can go wrong taken from real customer problems will be used to back up how simple guidelines and good use of available tools can make a massive difference to the performance, reliability, scalability and portability of your code. Data doesn’t have to be big to cause a problem, but as data sets grow, the way we access data has never been a more important consideration. Our customers work in scientific and high-performance computing with different trade offs to make between time-to-market, reliability and performance, but what they all have in common is that they have to care about I/O.
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