amdahl
3 free lessons tagged amdahl across Programming. Each one is a short sequence of focused steps with narration and a five-question quiz at the end — take them in any order, no signup required.
Measure First: The Arithmetic That Decides What to Optimise
Most optimisation effort is spent on code that was never the problem, and the reason is that intuition about where time goes is reliably wrong. This lesson covers why guessing fails, the arithmetic that caps what any optimisation can buy, the difference between latency and throughput, and how to set a target that tells you when to stop.
Threads and Shared State
Threads look deceptively simple — create a few, share some memory, done. In practice, shared mutable state is a minefield: race conditions, non-deterministic output, and bugs that vanish under a debugger. This lesson dissects concurrency vs parallelism, why `count++` is three operations the CPU can interleave, Amdahl's law, and what a critical section actually means.
Parallel Computing Fundamentals: CPUs, GPUs, Latency vs Throughput
Why GPUs eat CPUs for breakfast on some workloads and choke on others. Serial vs parallel execution, Amdahl's law, the latency-vs-throughput trade-off baked into silicon, and a rule of thumb for when to reach for a GPU.