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In some cases, you will lack benchmarking capabilities. connectivity, access, user count, latency) of geographic regions. Because pre-production environments are used for testing before an application is released to end users, teams have no access to real-user data. RUM generates a lot of data. Synthetic monitoring drawbacks.
These have inspired me to summarize another performance activity: evaluating benchmark accuracy. Accurate benchmarking rewards engineering investment that actually improves performance, but, unfortunately, inaccurate benchmarking is more common. If the benchmark reported 20k ops/sec, you should ask: why not 40k ops/sec?
These have inspired me to summarize another performance activity: evaluating benchmark accuracy. Accurate benchmarking rewards engineering investment that actually improves performance, but, unfortunately, inaccurate benchmarking is more common. If the benchmark reported 20k ops/sec, you should ask: why not 40k ops/sec?
Google’s industry benchmarks from 2018 also provide a striking breakdown of how each second of loading affects bounce rates. With all of this in mind, I thought improving the speed of my own version of a slow site would be a fun exercise. billion if the site slowed down by just one second. Source: Google /SOASTA Research, 2018.
The exercise seemed simple enough — just fix one item in the Colfax code and we should be finished. Each of the two vector units can issue one FMA instruction per cycle, assuming that there are enough independent accumulators to tolerate the 6-cycle dependent-operation latency. Instead, we found puzzle after puzzle.
There was no deep goal — just a desire to see the maximum GFLOPS in action. The exercise seemed simple enough — just fix one item in the Colfax code and we should be finished. Using the minimum number of accumulator registers needed to tolerate the pipeline latency (12), the assembly code for the inner loop is: B1.8:
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