Latency Numbers Every Programmer Should Know

latency.txt

Latency Comparison Numbers (~2012)
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L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD
Read 1 MB sequentially from memory     250,000   ns      250 us
Round trip within same datacenter      500,000   ns      500 us
Read 1 MB sequentially from SSD*     1,000,000   ns    1,000 us    1 ms  ~1GB/sec SSD, 4X memory
Disk seek                           10,000,000   ns   10,000 us   10 ms  20x datacenter roundtrip
Read 1 MB sequentially from disk    20,000,000   ns   20,000 us   20 ms  80x memory, 20X SSD
Send packet CA->Netherlands->CA    150,000,000   ns  150,000 us  150 ms

Notes
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1 ns = 10^-9 seconds
1 us = 10^-6 seconds = 1,000 ns
1 ms = 10^-3 seconds = 1,000 us = 1,000,000 ns

Credit
------
By Jeff Dean:               http://research.google.com/people/jeff/
Originally by Peter Norvig: http://norvig.com/21-days.html#answers

Contributions
-------------
'Humanized' comparison:  https://gist.github.com/hellerbarde/2843375
Visual comparison chart: http://i.imgur.com/k0t1e.png

As an updated point of reference for the first few numbers, Apple give a table in their Apple Silicon CPU Optimization guide. You can see they are extremely similar to the original figures:

Just a note for whomever wants to use this as a reference: I personally understand this does not take queuing & contention into account.

Numbers should change when physical devices have contention (CPU, Memory buffers, NIO, Thread pools) so things might be slightly larger in the average case (usually you'd try to maximize utilization and tradeoff for some contention) and quite larger on worst case (when that optimization goes wrong or you botched the design with bad bottlenecks).

This is amazing work btw and I'm glad to see how the community has added specs, references and notes on top of it.