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Add TRIMA implementation and benchmarks; optimize WMA with SIMD

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- Introduced `TrimaVector` class for multi-period Triangular Moving Average (TRIMA) calculations, optimized for SIMD.
- Implemented last-value substitution for invalid inputs in TRIMA.
- Added methods for calculating TRIMA for entire series and individual updates.
- Enhanced `Wma` class with periodic resync to prevent floating-point drift and introduced SIMD optimizations for performance.
- Updated benchmark suite to include TRIMA calculations alongside existing SMA, EMA, and WMA benchmarks.
This commit is contained in:
Miha Kralj
2025-12-04 13:05:56 -08:00
parent 5cc27c97de
commit 3ed35322a5
18 changed files with 2936 additions and 250 deletions
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perf/Benchmark.cs
+121 -5
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@@ -14,7 +14,7 @@ namespace QuanTAlib.Benchmarks;
public static class Program
{
public static void Main()
public static void Main(string[] args)
{
var config = ManualConfig.Create(DefaultConfig.Instance)
.AddJob(Job.ShortRun
@@ -24,12 +24,20 @@ public static class Program
.AddColumn(StatisticColumn.StdDev)
.HideColumns(Column.Job, Column.Error, Column.RatioSD);
BenchmarkRunner.Run<IndicatorBenchmarks>(config);
if (args.Length == 0)
{
BenchmarkRunner.Run<IndicatorBenchmarks>(config);
}
else
{
BenchmarkSwitcher.FromAssembly(typeof(Program).Assembly).Run(args, config);
}
}
}
[MemoryDiagnoser]
[MarkdownExporter, HtmlExporter]
[GroupBenchmarksBy(BenchmarkLogicalGroupRule.ByCategory)]
public class IndicatorBenchmarks
{
private const int BarCount = 200_000;
@@ -52,6 +60,9 @@ public class IndicatorBenchmarks
private double[][] _tulipWmaInputs = null!;
private double[] _tulipWmaOptions = null!;
private double[][] _tulipWmaOutputs = null!;
private double[][] _tulipTrimaInputs = null!;
private double[] _tulipTrimaOptions = null!;
private double[][] _tulipTrimaOutputs = null!;
// Pre-allocated outputs for QuanTAlib Span API
private double[] _quantalibOutput = null!;
@@ -98,55 +109,160 @@ public class IndicatorBenchmarks
_tulipWmaOptions = new double[] { Period };
_tulipWmaOutputs = new[] { new double[BarCount - smaLookback] };
_tulipTrimaInputs = new[] { _closeValues };
_tulipTrimaOptions = new double[] { Period };
_tulipTrimaOutputs = new[] { new double[BarCount - smaLookback] };
// Pre-allocate QuanTAlib output
_quantalibOutput = new double[BarCount];
}
// ==================== SMA ====================
[BenchmarkCategory("SMA")]
[Benchmark(Description = "QuanTAlib SMA (Span)")]
public void QuanTAlib_Sma_Span() => Sma.Calculate(_closeValues.AsSpan(), _quantalibOutput.AsSpan(), Period);
[BenchmarkCategory("SMA")]
[Benchmark(Description = "QuanTAlib SMA (TSeries)")]
public TSeries QuanTAlib_Sma_TSeries() => Sma.Calculate(_closeTseries, Period);
[BenchmarkCategory("SMA")]
[Benchmark(Description = "QuanTAlib SMA (Streaming)")]
public void QuanTAlib_Sma_Streaming()
{
var sma = new Sma(Period);
for (int i = 0; i < _closeValues.Length; i++)
{
_quantalibOutput[i] = sma.Update(new TValue(_closeTseries.Times[i], _closeValues[i])).Value;
}
}
[BenchmarkCategory("SMA")]
[Benchmark(Description = "Tulip SMA")]
public void Tulip_Sma() => Tulip.Indicators.sma.Run(_tulipSmaInputs, _tulipSmaOptions, _tulipSmaOutputs);
[BenchmarkCategory("SMA")]
[Benchmark(Description = "TALib SMA")]
public Core.RetCode TALib_Sma() => TALib.Functions.Sma<double>(_closeValues, 0..^0, _talibOutput, out _, Period);
[BenchmarkCategory("SMA")]
[Benchmark(Description = "Skender SMA")]
public List<SmaResult> Skender_Sma() => _quotes.GetSma(Period).ToList();
public double Skender_Sma()
{
double sum = 0;
foreach (var r in _quotes.GetSma(Period))
{
sum += (double)(r.Sma ?? 0);
}
return sum;
}
// ==================== EMA ====================
[BenchmarkCategory("EMA")]
[Benchmark(Description = "QuanTAlib EMA (Span)")]
public void QuanTAlib_Ema_Span() => Ema.Calculate(_closeValues.AsSpan(), _quantalibOutput.AsSpan(), Period);
[BenchmarkCategory("EMA")]
[Benchmark(Description = "QuanTAlib EMA (TSeries)")]
public TSeries QuanTAlib_Ema_TSeries() => Ema.Calculate(_closeTseries, Period);
[BenchmarkCategory("EMA")]
[Benchmark(Description = "QuanTAlib EMA (Streaming)")]
public void QuanTAlib_Ema_Streaming()
{
var ema = new Ema(Period);
for (int i = 0; i < _closeValues.Length; i++)
{
_quantalibOutput[i] = ema.Update(new TValue(_closeTseries.Times[i], _closeValues[i])).Value;
}
}
[BenchmarkCategory("EMA")]
[Benchmark(Description = "Tulip EMA")]
public void Tulip_Ema() => Tulip.Indicators.ema.Run(_tulipEmaInputs, _tulipEmaOptions, _tulipEmaOutputs);
[BenchmarkCategory("EMA")]
[Benchmark(Description = "TALib EMA")]
public Core.RetCode TALib_Ema() => TALib.Functions.Ema<double>(_closeValues, 0..^0, _talibOutput, out _, Period);
[BenchmarkCategory("EMA")]
[Benchmark(Description = "Skender EMA")]
public List<EmaResult> Skender_Ema() => _quotes.GetEma(Period).ToList();
public double Skender_Ema()
{
double sum = 0;
foreach (var r in _quotes.GetEma(Period))
{
sum += (double)(r.Ema ?? 0);
}
return sum;
}
// ==================== WMA ====================
[BenchmarkCategory("WMA")]
[Benchmark(Description = "QuanTAlib WMA (Span)")]
public void QuanTAlib_Wma_Span() => Wma.Calculate(_closeValues.AsSpan(), _quantalibOutput.AsSpan(), Period);
[BenchmarkCategory("WMA")]
[Benchmark(Description = "QuanTAlib WMA (TSeries)")]
public TSeries QuanTAlib_Wma_TSeries() => Wma.Calculate(_closeTseries, Period);
[BenchmarkCategory("WMA")]
[Benchmark(Description = "QuanTAlib WMA (Streaming)")]
public void QuanTAlib_Wma_Streaming()
{
var wma = new Wma(Period);
for (int i = 0; i < _closeValues.Length; i++)
{
_quantalibOutput[i] = wma.Update(new TValue(_closeTseries.Times[i], _closeValues[i])).Value;
}
}
[BenchmarkCategory("WMA")]
[Benchmark(Description = "Tulip WMA")]
public void Tulip_Wma() => Tulip.Indicators.wma.Run(_tulipWmaInputs, _tulipWmaOptions, _tulipWmaOutputs);
[BenchmarkCategory("WMA")]
[Benchmark(Description = "TALib WMA")]
public Core.RetCode TALib_Wma() => TALib.Functions.Wma<double>(_closeValues, 0..^0, _talibOutput, out _, Period);
[BenchmarkCategory("WMA")]
[Benchmark(Description = "Skender WMA")]
public List<WmaResult> Skender_Wma() => _quotes.GetWma(Period).ToList();
public double Skender_Wma()
{
double sum = 0;
foreach (var r in _quotes.GetWma(Period))
{
sum += (double)(r.Wma ?? 0);
}
return sum;
}
// ==================== TRIMA ====================
[BenchmarkCategory("TRIMA")]
[Benchmark(Description = "QuanTAlib TRIMA (Span)")]
public void QuanTAlib_Trima_Span() => Trima.Calculate(_closeValues.AsSpan(), _quantalibOutput.AsSpan(), Period);
[BenchmarkCategory("TRIMA")]
[Benchmark(Description = "QuanTAlib TRIMA (TSeries)")]
public TSeries QuanTAlib_Trima_TSeries() => Trima.Calculate(_closeTseries, Period);
[BenchmarkCategory("TRIMA")]
[Benchmark(Description = "QuanTAlib TRIMA (Streaming)")]
public void QuanTAlib_Trima_Streaming()
{
var trima = new Trima(Period);
for (int i = 0; i < _closeValues.Length; i++)
{
_quantalibOutput[i] = trima.Update(new TValue(_closeTseries.Times[i], _closeValues[i])).Value;
}
}
[BenchmarkCategory("TRIMA")]
[Benchmark(Description = "Tulip TRIMA")]
public void Tulip_Trima() => Tulip.Indicators.trima.Run(_tulipTrimaInputs, _tulipTrimaOptions, _tulipTrimaOutputs);
[BenchmarkCategory("TRIMA")]
[Benchmark(Description = "TALib TRIMA")]
public Core.RetCode TALib_Trima() => TALib.Functions.Trima<double>(_closeValues, 0..^0, _talibOutput, out _, Period);
}