This is a Java port of Daniel Lemire's fast_double_parser.
import ch.randelshofer.fastdoubleparser.FastDoubleParser;
import ch.randelshofer.fastdoubleparser.FastFloatParser;
double d = FastDoubleParser.parseDouble("1.2345");
float f = FastFloatParser.parseFloat("1.2345");Method parseDouble() takes a CharacterSequence, a char-array or a byte-array as argument. Therefore, you can
parse from a StringBuffer or an array without having to convert your input to a String. Parsing from an array is
faster, because the parser can process multiple characters at once using SIMD instructions.
When you clone the code repository from GitHub, you can choose from the following branches:
main: The code in this branch requires Java 17.java8: The code in this branch requires Java 8.dev: This code may or may not work. This code uses the experimental Vector API, and the Foreign Memory Access API, that are included in Java 19.
How to run the performance tests on a Mac:
- Install Java JDK 8 or higher. for example OpenJDK Java 18
- Install the XCode command line tools from Apple.
- Open the Terminal and execute the following commands:
git clone https://github.com/wrandelshofer/FastDoubleParser.git
cd FastDoubleParser
javac -d out -encoding utf8 --module-source-path src/main/java --module ch.randelshofer.fastdoubleparser
javac -d out -encoding utf8 -p out --module-source-path FastDoubleParserDemo/src/main/java --module ch.randelshofer.fastdoubleparserdemo
java -p out -m ch.randelshofer.fastdoubleparserdemo/ch.randelshofer.fastdoubleparserdemo.Main
java -p out -m ch.randelshofer.fastdoubleparserdemo/ch.randelshofer.fastdoubleparserdemo.Main data/canada.txt git clone https://github.com/wrandelshofer/FastDoubleParser.git
cd FastDoubleParser
git checkout java8
mkdir out
javac -d out -encoding utf8 -sourcepath src/main/java/ch.randelshofer.fastdoubleparser src/main/java/ch.randelshofer.fastdoubleparser/**/*.java
javac -d out -encoding utf8 -cp out -sourcepath FastDoubleParserDemo/src/main/java/ch.randelshofer.fastdoubleparserdemo FastDoubleParserDemo/src/main/java/ch.randelshofer.fastdoubleparserdemo/**/*.java
java -cp out ch.randelshofer.fastdoubleparserdemo.Main
java -cp out ch.randelshofer.fastdoubleparserdemo.Main data/canada.txt On my Mac mini (2018) I get the results shown below. The speedup factor with respect to Double.parseDouble ranges from
0.5 to 6 depending on the shape of the input data. You can expect a speedup factor of 4 for common input data shapes.
WARNING: Using incubator modules: jdk.incubator.vector
Intel(R) Core(TM) i7-8700B CPU @ 3.20GHz SIMD-256
x86_64. Mac OS X. 12.4. 12
OpenJDK 64-Bit Server VM. Oracle Corporation. 19-ea+33-2224
-XX:+UnlockExperimentalVMOptions
parsing random doubles in the range [0.1)
Trying to reach a confidence level of 99.8 % which only deviates by 1 % from the average measured duration.
FastDouble String : 573.48 MB/s (+/- 6.3 %) 32.92 Mfloat/s 30.38 ns/f
FastDouble char[] : 606.53 MB/s (+/- 5.9 %) 34.82 Mfloat/s 28.72 ns/f
FastDouble byte[] : 689.95 MB/s (+/- 4.7 %) 39.60 Mfloat/s 25.25 ns/f
Double : 95.66 MB/s (+/- 2.3 %) 5.49 Mfloat/s 182.12 ns/f
FastFloat String : 533.88 MB/s (+/- 2.3 %) 30.65 Mfloat/s 32.63 ns/f
FastFloat char[] : 631.52 MB/s (+/- 4.1 %) 36.25 Mfloat/s 27.59 ns/f
FastFloat byte[] : 689.57 MB/s (+/- 4.9 %) 39.58 Mfloat/s 25.26 ns/f
Float : 101.22 MB/s (+/- 2.6 %) 5.81 Mfloat/s 172.11 ns/f
Speedup FastDouble String vs Double: 6.00
Speedup FastDouble char[] vs Double: 6.34
Speedup FastDouble byte[] vs Double: 7.21
Speedup FastFloat String vs Double: 5.58
Speedup FastFloat char[] vs Double: 6.60
Speedup FastFloat byte[] vs Double: 7.21
Speedup Float vs Double: 1.06
'
parsing numbers in file /Users/Shared/Developer/Java/FastDoubleParser/github/FastDoubleParser/data/canada.txt
read 111126 lines
Trying to reach a confidence level of 99.8 % which only deviates by 1 % from the average measured duration.
FastDouble String : 432.57 MB/s (+/- 3.4 %) 24.86 Mfloat/s 40.23 ns/f
FastDouble char[] : 550.44 MB/s (+/- 3.5 %) 31.63 Mfloat/s 31.61 ns/f
FastDouble byte[] : 578.14 MB/s (+/- 3.1 %) 33.22 Mfloat/s 30.10 ns/f
Double : 82.24 MB/s (+/- 3.0 %) 4.73 Mfloat/s 211.60 ns/f
FastFloat String : 430.42 MB/s (+/- 2.9 %) 24.73 Mfloat/s 40.43 ns/f
FastFloat char[] : 547.38 MB/s (+/- 4.7 %) 31.46 Mfloat/s 31.79 ns/f
FastFloat byte[] : 590.19 MB/s (+/- 4.9 %) 33.92 Mfloat/s 29.48 ns/f
Float : 101.20 MB/s (+/- 2.2 %) 5.82 Mfloat/s 171.95 ns/f
Speedup FastDouble String vs Double: 5.26
Speedup FastDouble char[] vs Double: 6.69
Speedup FastDouble byte[] vs Double: 7.03
Speedup FastFloat String vs Double: 5.23
Speedup FastFloat char[] vs Double: 6.66
Speedup FastFloat byte[] vs Double: 7.18
Speedup Float vs Double: 1.23
FastDoubleParser also speeds up parsing of hexadecimal float literals:
parsing numbers in file /Users/Shared/Developer/Java/FastDoubleParser/github/FastDoubleParser/data/canada_hex.txt
read 111126 lines
Trying to reach a confidence level of 99.8 % which only deviates by 1 % from the average measured duration.
FastDouble String : 406.00 MB/s (+/- 8.9 %) 22.26 Mfloat/s 44.92 ns/f
FastDouble char[] : 631.42 MB/s (+/-11.6 %) 34.62 Mfloat/s 28.88 ns/f
FastDouble byte[] : 618.98 MB/s (+/- 2.0 %) 33.94 Mfloat/s 29.46 ns/f
Double : 52.61 MB/s (+/- 7.3 %) 2.88 Mfloat/s 346.70 ns/f
FastFloat String : 410.53 MB/s (+/-10.2 %) 22.51 Mfloat/s 44.43 ns/f
FastFloat char[] : 628.19 MB/s (+/-12.0 %) 34.44 Mfloat/s 29.03 ns/f
FastFloat byte[] : 615.30 MB/s (+/- 8.4 %) 33.74 Mfloat/s 29.64 ns/f
Float : 53.78 MB/s (+/- 4.0 %) 2.95 Mfloat/s 339.15 ns/f
Speedup FastDouble String vs Double: 7.72
Speedup FastDouble char[] vs Double: 12.00
Speedup FastDouble byte[] vs Double: 11.77
Speedup FastFloat String vs Double: 7.80
Speedup FastFloat char[] vs Double: 11.94
Speedup FastFloat byte[] vs Double: 11.70
Speedup Float vs Double: 1.02
The Y-axis shows Mfloat/s.
| Method | 1.8.0_281 | 11.0.8 | 18.0.1.1 | 19-ea | 17.0.3graalvm |
|---|---|---|---|---|---|
| Double | 4.86 | 5.34 | 5.09 | 5.28 | 6.96 |
| FastDouble String | 20.30 | 27.83 | 31.18 | 32.59 | 32.74 |
| FastDouble char[] | 30.60 | 30.68 | 33.58 | 37.20 | 34.32 |
| FastDouble byte[] | 31.29 | 35.61 | 38.24 | 39.67 | 40.21 |
For comparison. here are the test results
of simple_fastfloat_benchmark
on the same computer:
version: Thu Mar 31 10:18:12 2022 -0400 f2082bf747eabc0873f2fdceb05f9451931b96dc
Intel(R) Core(TM) i7-8700B CPU @ 3.20GHz SIMD-256
$ ./build/benchmarks/benchmark
# parsing random numbers
available models (-m): uniform one_over_rand32 simple_uniform32 simple_int32 int_e_int simple_int64 bigint_int_dot_int big_ints
model: generate random numbers uniformly in the interval [0.0.1.0]
volume: 100000 floats
volume = 2.09808 MB
netlib : 317.31 MB/s (+/- 6.0 %) 15.12 Mfloat/s 66.12 ns/f
doubleconversion : 263.89 MB/s (+/- 4.2 %) 12.58 Mfloat/s 79.51 ns/f
strtod : 86.13 MB/s (+/- 3.7 %) 4.10 Mfloat/s 243.61 ns/f
abseil : 467.27 MB/s (+/- 9.0 %) 22.27 Mfloat/s 44.90 ns/f
fastfloat : 880.79 MB/s (+/- 6.6 %) 41.98 Mfloat/s 23.82 ns/f
OpenJDK 19-ea+33-2224
FastDouble String : 566.18 MB/s (+/- 1.2 %) 32.50 Mfloat/s 30.77 ns/f
FastDouble char[] : 606.77 MB/s (+/- 3.6 %) 34.83 Mfloat/s 28.71 ns/f
FastDouble byte[] : 692.78 MB/s (+/- 2.2 %) 39.77 Mfloat/s 25.14 ns/f
Double : 98.41 MB/s (+/- 2.6 %) 5.65 Mfloat/s 176.99 ns/f
'
$ ./build/benchmarks/benchmark -f data/canada.txt
# read 111126 lines
volume = 1.93374 MB
netlib : 337.79 MB/s (+/- 5.8 %) 19.41 Mfloat/s 51.52 ns/f
doubleconversion : 254.22 MB/s (+/- 6.0 %) 14.61 Mfloat/s 68.45 ns/f
strtod : 73.33 MB/s (+/- 7.1 %) 4.21 Mfloat/s 237.31 ns/f
abseil : 411.11 MB/s (+/- 7.3 %) 23.63 Mfloat/s 42.33 ns/f
fastfloat : 741.32 MB/s (+/- 5.3 %) 42.60 Mfloat/s 23.47 ns/f
OpenJDK 19-ea+33-2224
FastDouble String : 430.24 MB/s (+/- 0.8 %) 24.72 Mfloat/s 40.45 ns/f
FastDouble char[] : 512.85 MB/s (+/- 7.0 %) 29.47 Mfloat/s 33.93 ns/f
FastDouble byte[] : 515.65 MB/s (+/- 4.2 %) 29.63 Mfloat/s 33.75 ns/f
Double : 87.33 MB/s (+/- 4.0 %) 5.02 Mfloat/s 199.27 ns/f