07-28-2022, 01:38 AM
Simulation helps poke at cache sizes without buying new silicon. I adjust associativity levels and track hit rates across workloads. You see how prefetchers cut down latency in certain patterns. And sometimes a small change in replacement policy boosts overall speed a lot. But you must validate against real traces or the numbers drift. Perhaps adding out of order execution shows gains in parallel tasks.
Power draw comes into play when you simulate voltage scaling on cores. I monitor heat buildup during heavy compute bursts. You compare single thread versus multi thread behaviors side by side. Or the interconnect bandwidth limits data movement between units. Then results highlight where energy gets wasted most. Simulation lets you explore instruction sets and their impacts on code density. I test vector extensions against scalar loops for throughput edges. You find branch predictors reduce wasted cycles in loops. But complex models take longer to execute fully.
Perhaps you layer in network effects for distributed setups. I crunch cycle accurate traces from apps to find hot spots. You adjust buffer depths and see queue overflows vanish. And that reveals tradeoffs in area versus performance. Simulation gives quick feedback on architecture tweaks before hardware spins. I explore superscalar designs and their issue widths. You notice how speculation affects correctness under errors. But careful calibration keeps outputs trustworthy across runs.
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