C# port of Daniel Lemire's fast_float fully ported from C++ to C#. It is almost 7 times faster than the standard library in some cases while providing exact results.
We use the realistic files in /data. The mesh.txt data file contains numbers that are easier to parse whereas the canada.txt data file is representative of a more challenging scenario. We compare the Double.Parse() function from the runtime library with our FastFloat.ParseDouble() function. The ParseNumberString() only function parses the string itself without any float computation: it might represent an upper bound on the possible performance.
BenchmarkDotNet=v0.12.1, OS=ubuntu 20.04 (container)
AMD EPYC 7262, 1 CPU, 16 logical and 8 physical cores
.NET Core SDK=5.0.102
[Host] : .NET Core 5.0.2 (CoreCLR 5.0.220.61120, CoreFX 5.0.220.61120), X64 RyuJIT
.NET Core 5.0 : .NET Core 5.0.2 (CoreCLR 5.0.220.61120, CoreFX 5.0.220.61120), X64 RyuJIT
Job=.NET Core 5.0 Runtime=.NET Core 5.0
| Method | FileName | Mean | Error | StdDev | Min | Ratio | MFloat/s | MB/s |
|--------------------------- |---------------- |----------:|----------:|----------:|----------:|------:|---------:|---------:|
| FastFloat.ParseDouble() | data/canada.txt | 5.140 ms | 0.0280 ms | 0.0262 ms | 5.105 ms | 0.14 | 21.77 | 408.99 |
| 'ParseNumberString() only' | data/canada.txt | 2.540 ms | 0.0053 ms | 0.0047 ms | 2.531 ms | 0.07 | 43.90 | 824.87 |
| Double.Parse() | data/canada.txt | 37.147 ms | 0.3284 ms | 0.3071 ms | 36.443 ms | 1.00 | 3.05 | 57.29 |
| | | | | | | | | |
| FastFloat.ParseDouble() | data/mesh.txt | 2.083 ms | 0.0029 ms | 0.0024 ms | 2.080 ms | 0.29 | 35.10 | 298.07 |
| 'ParseNumberString() only' | data/mesh.txt | 1.298 ms | 0.0034 ms | 0.0032 ms | 1.294 ms | 0.18 | 56.45 | 479.30 |
| Double.Parse() | data/mesh.txt | 7.086 ms | 0.0911 ms | 0.0852 ms | 6.931 ms | 1.00 | 10.54 | 89.45 |
In this repo FastFloatTestBench we demonstrate a concrete performance gain obtained with FastFloat.ParseDouble() with the CSVHelper library. This is one of the fastest CSV parser available.
Single and multiple columns files have been tested. :
- Canada.txt and mesh.txt are the same from previous benchmark.
- Syntethic.csv is composed of 150 000 random floats.
- World cities population data (100k/300k) are real data obtained from OpenDataSoft.
Benchmark is run on same environment.
BenchmarkDotNet=v0.12.1, OS=ubuntu 20.04 (container)
AMD EPYC 7262, 1 CPU, 16 logical and 8 physical cores
.NET Core SDK=5.0.102
[Host] : .NET Core 5.0.2 (CoreCLR 5.0.220.61120, CoreFX 5.0.220.61120), X64 RyuJIT
.NET Core 5.0 : .NET Core 5.0.2 (CoreCLR 5.0.220.61120, CoreFX 5.0.220.61120), X64 RyuJIT
Job=.NET Core 5.0 Runtime=.NET Core 5.0
| Method | fileName | fileSize | nbFloat | Mean | Error | StdDev | Min | Ratio | MFloat/s |
|-------------------------------------- |----------------------- |--------- |-------- |----------:|---------:|---------:|----------:|------:|---------:|
| 'Double.Parse() - singlecol' | TestData/canada.txt | 2088 | 111126 | 84.46 ms | 0.271 ms | 0.226 ms | 84.16 ms | 1.00 | 1.32 |
| 'Zeroes - singlecol' | TestData/canada.txt | 2088 | 111126 | 33.59 ms | 0.214 ms | 0.178 ms | 33.21 ms | 0.40 | 3.35 |
| 'FastFloat.ParseDouble() - singlecol' | TestData/canada.txt | 2088 | 111126 | 40.58 ms | 0.265 ms | 0.235 ms | 40.13 ms | 0.48 | 2.77 |
| | | | | | | | | | |
| 'Double.Parse() - singlecol' | TestData/mesh.txt | 691 | 73019 | 29.64 ms | 0.157 ms | 0.146 ms | 29.41 ms | 1.00 | 2.48 |
| 'Zeroes - singlecol' | TestData/mesh.txt | 691 | 73019 | 17.68 ms | 0.077 ms | 0.064 ms | 17.58 ms | 0.60 | 4.15 |
| 'FastFloat.ParseDouble() - singlecol' | TestData/mesh.txt | 691 | 73019 | 20.06 ms | 0.188 ms | 0.176 ms | 19.82 ms | 0.68 | 3.68 |
| | | | | | | | | | |
| 'Double.Parse() - singlecol' | TestData/synthetic.csv | 2969 | 150000 | 114.10 ms | 1.355 ms | 1.202 ms | 111.87 ms | 1.00 | 1.34 |
| 'Zeroes - singlecol' | TestData/synthetic.csv | 2969 | 150000 | 46.48 ms | 0.197 ms | 0.184 ms | 46.20 ms | 0.41 | 3.25 |
| 'FastFloat.ParseDouble() - singlecol' | TestData/synthetic.csv | 2969 | 150000 | 54.29 ms | 0.683 ms | 0.605 ms | 53.40 ms | 0.48 | 2.81 |
| | | | | | | | | | |
| 'Double.Parse() - multicol' | TestData/w-c-100K.csv | 4842 | 200002 | 182.30 ms | 2.629 ms | 2.459 ms | 179.70 ms | 1.00 | 1.11 |
| 'Zeroes() - multicol' | TestData/w-c-100K.csv | 4842 | 200002 | 160.47 ms | 1.368 ms | 1.068 ms | 158.88 ms | 0.88 | 1.26 |
| 'FastFloat.Parse() - multicol' | TestData/w-c-100K.csv | 4842 | 200002 | 168.60 ms | 1.217 ms | 1.079 ms | 166.84 ms | 0.92 | 1.20 |
| | | | | | | | | | |
| 'Double.Parse() - multicol' | TestData/w-c-300K.csv | 14526 | 600002 | 572.31 ms | 4.286 ms | 3.799 ms | 566.87 ms | 1.00 | 1.06 |
| 'Zeroes() - multicol' | TestData/w-c-300K.csv | 14526 | 600002 | 451.54 ms | 3.379 ms | 2.822 ms | 445.87 ms | 0.79 | 1.35 |
| 'FastFloat.Parse() - multicol' | TestData/w-c-300K.csv | 14526 | 600002 | 479.76 ms | 3.103 ms | 2.423 ms | 477.05 ms | 0.84 | 1.26 |
.NET Core 3.1 or better. Under .NET 5 framework, the library takes advantage of the new Math.BigMul() function.
As this library targets multiple framework, you can specify the target framework version with -f parameter :
dotnet build -c Release -f net5.0
dotnet test -f net5.0
If you omit the target framework and you don't have both .net 5.0 and dotnetcore 3.1 SDKs installed you may experience an error when building or running tests.
The set of unit tests in /TestcsFastFloat project combines unit tests from many libraries. It includes tests used by the Go Team. Additionnal info on Nigel Tao's work can be found here.
Some unit tests are based on Approvals.net library. They require a diff tool installed on your computer. Tests will be automatically skiped if no diff tool is found.
Two functions are available: FastDoubleParser.ParseDouble and FastFloatParser.ParseFloat. Since v3.0, TryParse pattern is supported for each function.
String, char * and ReadOnlySpan<char> are supported inputs.
using csFastFloat;
double x;
float y;
double answer = 0;
foreach (string l in lines)
{
x = FastDoubleParser.ParseDouble(l);
y = FastFloatParser.ParseFloat(l);
}Input strings are expected to be valid UTF-16.
Trailing content in the string is ignored. You may pass an optional out int characters_consumed parameter
FastDoubleParser.ParseDouble(l, out int characters_consumed) if you wich to check how many characters were processed. Some users may want to fail when the number of characters consumed does not match the string length.
For UTF-8 or ASCII inputs, you may pass a ReadOnlySpan<byte> argument. You can also pass
an optional out int characters_consumed parameter to track the number of characters consumed
by the number pattern.
This library is the main project in my master's degree under the direction of Professor Daniel Lemire at TELUQ University. A special thanks to Egor Bogatov and all contributors for their really meaningful contribution.
- Daniel Lemire, Number Parsing at a Gigabyte per Second, arXiv:2101.11408