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Minor typo fixes

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Added a comma to one sentence, otherwise this is markdown
issues (escape a _, match a backtick) and a couple of spellings
of "contended" as "contented". (I hope that one isn't
to contentious, but I contend that the content isn't
changed and I'm content with it, also English is a mistake.)
This commit is contained in:
Seebs 2018-09-26 23:46:10 -05:00 committed by Damian Gryski
parent f3fbdafab4
commit 2b24ff3590
1 changed files with 7 additions and 7 deletions
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performance.md
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@ -357,10 +357,10 @@ not realized in the production system due to cache contention (e.g., lookup
tables are in the processor cache during benchmarking but always flushed by tables are in the processor cache during benchmarking but always flushed by
"real data" when used in a real system. "real data" when used in a real system.
Google's [Jump Hash paper](https://arxiv.org/pdf/1406.2294.pdf) in fact Google's [Jump Hash paper](https://arxiv.org/pdf/1406.2294.pdf) in fact
addressed this directly, comparing performance on both a contented and addressed this directly, comparing performance on both a contended and
uncontended processor cache. (See graphs 4 and 5 in the Jump Hash paper) uncontended processor cache. (See graphs 4 and 5 in the Jump Hash paper)
TODO: how to simulate a contented cache, show incremental cost TODO: how to simulate a contended cache, show incremental cost
Another aspect to consider is data-transfer time. Generally network and disk Another aspect to consider is data-transfer time. Generally network and disk
access is very slow, and so being able to load a compressed chunk will be access is very slow, and so being able to load a compressed chunk will be
@ -650,7 +650,7 @@ improve allowing you to stop when you hit an acceptable limit.
Cache common cases: Cache common cases:
* Your cache doesn't even need to be huge. * Your cache doesn't even need to be huge.
* see `time.Parse() example below; just a single value made an impact * see `time.Parse()` example below; just a single value made an impact
* But beware cache invalidation, thread issues, etc. * But beware cache invalidation, thread issues, etc.
* Random cache eviction is fast and sufficiently effective. * Random cache eviction is fast and sufficiently effective.
* Random cache insertion can limit cache to popular items with minimal logic. * Random cache insertion can limit cache to popular items with minimal logic.
@ -724,9 +724,9 @@ where your program crashes, slows down, or starts returning incorrect data
as the system evolves. as the system evolves.
Program tuning improvements are cumulative. 5x 3% improvements is a 15% Program tuning improvements are cumulative. 5x 3% improvements is a 15%
improvement. Making optimizations it's worth it to think about the expected improvement. When making optimizations, it's worth it to think about the
performance improvement. Replacing a hash function with a faster one is a expected performance improvement. Replacing a hash function with a faster one
constant factor improvement. is a constant factor improvement.
Understanding your requirements and where they can be altered can lead to Understanding your requirements and where they can be altered can lead to
performance improvements. One issue that was presented in the \#performance performance improvements. One issue that was presented in the \#performance
@ -835,7 +835,7 @@ Techniques applicable to source code in general
1. How to read it pprof output 1. How to read it pprof output
1. What are the different pieces of the runtime that show up 1. What are the different pieces of the runtime that show up
* malloc, gc workers * malloc, gc workers
* runtime._ExternalCode * runtime.\_ExternalCode
1. Macro-benchmarks (Profiling in production) 1. Macro-benchmarks (Profiling in production)
* net/http/pprof * net/http/pprof
1. Using -base to look at differences 1. Using -base to look at differences