Speedup
Speedup is the ratio of a baseline execution time to an alternative execution time for the same computation.
Grokking Concurrency
Speedup is the ratio comparing the time required by a baseline execution with the time required by a parallel execution.
- How it is used
- Measures the performance benefit of parallel execution against an optimal sequential baseline.
- How deep it goes
- Explains fixed-work and fixed-time interpretations, bottlenecks, and a process-pool measurement without deriving a formal law.
- Examples
- Uses card sorting, shopping checkout lines, and Python password cracking to illustrate bottlenecks and measured gains.
- What you can do after
- Evaluate parallel designs by comparing execution times, identifying sequential limits, and interpreting throughput-oriented gains.
Learn Concurrent Programming with Go
Speedup is the ratio of a computation's execution time in a baseline configuration to its execution time in an improved or parallel configuration.
- How it is used
- Uses speedup to evaluate parallel performance, processor scalability, and the effect of sequential work.
- How deep it goes
- Explains speedup through Amdahl’s and Gustafson’s laws, examples, and figures, but stops short of deriving their formulas.
- Examples
- Illustrates speedup with house construction, builders, narrow-road transport, and a computer game’s frame rate and graphics.
- What you can do after
- Evaluate/understand why adding processors eventually produces diminishing returns or supports larger workloads.
Read how Learn Concurrent Programming with Go explains speedup →
Related concepts
- Amdahl’s Lawmeasured by · Amdahl’s Law describes how the speedup from optimizing or parallelizing a computation is limited by the fraction that remains sequential or unoptimized.
- key-value cacheproduced by · A key-value cache is a data structure that stores previously computed transformer attention keys and values for reuse during subsequent token generation.
- throughputmeasures · The amount of work, data, or output a system processes or completes per unit of time.
- parallelismproduced by · Parallelism is the concurrent execution of multiple computational operations, often across multiple processing resources.
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