public T Run <T>(BenchmarkOptions <T> options)
{
var batchAmounts = 32;
var batchSize = options.BatchSize;
List <T> batchRunResults = new List <T> {
};
while (true)
{
// TODO: maybe it's better to increase batchAmount * 2/3 at each iteration - this can help parallelization
// TODO: maybe it's better to increase batchSize at each iteration + merge previous batches - this can reduce overall memory usage
batchRunResults.AddRange(
ParallelEnumerable.Range(0, batchAmounts)
.Select(_ => RunOnce(options, batchSize)));
if (!IsGoodEnough(options, batchRunResults))
{
continue;
}
else
{
break;
}
}
Console.WriteLine($"Total runs: {batchRunResults.Count * batchSize}");
return(batchRunResults.Aggregate(options.Combine));
}
private static bool IsGoodEnough <T>(BenchmarkOptions <T> options, List <T> batchRunResults)
{
return(options.QuantifiedValues.All(valueOptions => IsGoodEnough(valueOptions, batchRunResults)));
}
private static T RunOnce <T>(BenchmarkOptions <T> options, int runs)
{
return(ParallelEnumerable.Range(0, runs)
.Select(_ => options.RunOnce())
.Aggregate(options.Seed, options.Combine));
}
