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jhudsl / Computing_for_Cancer_Informatics

The course covers the key underlying principles and concepts in computing. It covers concrete discussions of the differences between cloud and local computing. The course highlights a number of computing options and etiquette for using shared resources.
https://jhudatascience.org/Computing_for_Cancer_Informatics
Creative Commons Attribution 4.0 International
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add this? #88

Open carriewright11 opened 1 year ago

carriewright11 commented 1 year ago

https://www.computerhistory.org/timeline/memory-storage/

carriewright11 commented 1 year ago

and this from the what I wrote for the podcast : To give you a sense of how much data sizes have changed over time, consider the fact that the average word document is generally say about 26 Kilo bytes. Kilo meaning 1000 - 1000 bytes. Previous processed datasets for gene expression (using technology called microarray) would be in this range or in the mega byte range (1 million bytes) . However, RNA seq and even larger single cell RNA seq, has files in the range of Giga bytes - Giga meaning 1 billion bytes. With about 20 samples we can reach up to terabyte levels worth of data - which is about the storage capacity of a current modern laptop! On the order of 1 trillion bytes.

The growth in our computing capacity is incredible. Our typical personal computers today - even our phones, are equivalent or better than the institutional supercomputers of the past. Much of this has to do with the size of transistors getting smaller and more and more transistors being added to computers. In the past transistors in computers were in the range of centimeters in size and could be seen in my hand across the room. Now they are at the nanometer scale- so they are microscopic (similar to the size of proteins in cells). Computers went from having a thousand transistors to having millions to billions. This enables them to work with much larger files.