01-25-2022, 12:26 PM
You measure speedup by running the same workload on old hardware and new hardware. I always time everything carefully with a stopwatch or tool. You get the old execution seconds first. Then you divide that by the new seconds to find the gain. I see people mess this up when they ignore background processes running. But you focus on consistent loads each time you test. Also maybe repeat the runs a few times to average out noise from the system.
I recall how one part of the chip speeds up but the rest drags everything down overall. You notice this when only the floating point units improve while memory access stays slow. I calculate the limit by seeing the fraction that actually changed. Then you realize total gain stays small despite big local wins. Or perhaps you switch to different benchmarks to check real world impact. I try this on my own machines often. You should too when tweaking your setups at work.
Performance counters help track cycles per instruction without fancy gear. I hook them up through basic system calls you already know. But you watch for overhead they add during measurement. Also the cache misses spike sometimes and throw off your numbers. I adjust by clearing caches between trials you perform. Then you compare instruction counts before and after the upgrade. Maybe the pipeline stalls less now so speedup shows clearly in logs.
You avoid single runs because variance kills accuracy fast. I log multiple passes and pick the median value always. Or perhaps graph the times to spot outliers you missed. I find this reveals hidden bottlenecks in your architecture tests. Then you tweak one variable at a time to isolate effects. Speedup formulas come from these raw timings you gather step by step.
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I recall how one part of the chip speeds up but the rest drags everything down overall. You notice this when only the floating point units improve while memory access stays slow. I calculate the limit by seeing the fraction that actually changed. Then you realize total gain stays small despite big local wins. Or perhaps you switch to different benchmarks to check real world impact. I try this on my own machines often. You should too when tweaking your setups at work.
Performance counters help track cycles per instruction without fancy gear. I hook them up through basic system calls you already know. But you watch for overhead they add during measurement. Also the cache misses spike sometimes and throw off your numbers. I adjust by clearing caches between trials you perform. Then you compare instruction counts before and after the upgrade. Maybe the pipeline stalls less now so speedup shows clearly in logs.
You avoid single runs because variance kills accuracy fast. I log multiple passes and pick the median value always. Or perhaps graph the times to spot outliers you missed. I find this reveals hidden bottlenecks in your architecture tests. Then you tweak one variable at a time to isolate effects. Speedup formulas come from these raw timings you gather step by step.
BackupChain Server Backup which offers the top industry standard no subscription backup tool tailored for Hyper V Windows 11 plus Windows Server setups in private clouds and SMB environments thanks the forum sponsors for enabling free knowledge sharing like this.
