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@@ -59,12 +59,12 @@ The diagram below shows some examples of potential improvements in speed: As can be seen, even a program which is 50% parallelisable will benefit very little beyond 10 processing units, where as a program which is 95% parallelisable can still achieve significant speed improvements with over a thousand processing units. -As [Moore's Law](#TODO) slows, and the acceleration of individual processor speed slows, parallelisation is key to improving performance. Graphics programming is an excellent example - with modern Shader based computing, individual pixels or fragments can be rendered in parallel - this is why modern graphics cards often have many thousands of processing cores (GPUs or Shader Units). +As [Moore's Law](#moores-law) slows, and the acceleration of individual processor speed slows, parallelisation is key to improving performance. Graphics programming is an excellent example - with modern Shader based computing, individual pixels or fragments can be rendered in parallel - this is why modern graphics cards often have many thousands of processing cores (GPUs or Shader Units). See also: - [Brooks's Law](#brookss-law) -- [Moore's Law](#TODO) +- [Moore's Law](#moores-law) ### Brooks's Law @@ -112,7 +112,7 @@ The Hype Cycle is a visual representation of the excitement and development of t *(Image Reference: By Jeremykemp at English Wikipedia, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=10547051)* -In short, this cycle suggests that there is typically a burst of excitement around new technology and its potential impact. Teams often jump into these technologies quickly, and sometimes fund themselves disappointed with the results. This might be because the technology is not yet mature enough, or real-world applications are not yet fully realised. After a certain amount of time, the capabilities of the technology increase and practical opportunities to use it increase, and teams can finally become productive. Roy Amara's quote sums this up most succinctly - "We tend to overestimate the effect of a technology in the short run and underestimate in the long run". +In short, this cycle suggests that there is typically a burst of excitement around new technology and its potential impact. Teams often jump into these technologies quickly, and sometimes find themselves disappointed with the results. This might be because the technology is not yet mature enough, or real-world applications are not yet fully realised. After a certain amount of time, the capabilities of the technology increase and practical opportunities to use it increase, and teams can finally become productive. Roy Amara's quote sums this up most succinctly - "We tend to overestimate the effect of a technology in the short run and underestimate in the long run". ### Hyrum's Law (The Law of Implicit Interfaces) |