Provides java.util.Random extension for Linux and Mac OSX wrapping Intel's Digital Random Number Generator (DRNG) known as Intel Secure Key, a name for its RDRAND instruction accessible via its free library librdrand, using JNI.
First things first, a disclaimer: Neither I nor this utility are associated with or endorsed by Intel in any shape or form. Glad we got that out of the way, now to business.
You can get details on Intel's RNG implementation here. This utility wraps functionality provided by RDRAND useful in the Java context via an extension of the standard interface java.util.Random. Simple and clean, runs in user land, no root access is required, nor is any sys admin support required for shared library deployments, that is handled internally dynamically.
Intel claims RDRAND is cryptographically strong and its hardware based implementation with a sealed seed/re-seed implementation eliminates many attack vectors possible for other RNGs, it also successfully passed the Dieharder tests as detailed below, however, it is a closed source implementation on chip so the true efficacy of the implementation cannot be verified independently. Nor is it possible to rule out any potential back doors implemented for the NSA as has been speculated by some around the web (although access to any such back door either physically or remotely would imply a serious breach of security that means you are already owned and compromise of your RNG is the least of your worries).
It is however being integrated in the Linux Kernel (3.12) as one of the sources for the entropy pool and like any black box implementation being used in a cryptographically sensitive environment, it should be tested regularly for randomness.
For those who would prefer a full open source RNG and for existing users of Uncommons Maths, version 1.1.0 of the utility provides an implementation of org.uncommons.maths.random.SeedGenerator using RDRAND which can be used as the seed source for any of the Uncommons Maths RNGs.
Since RDRAND cannot be seeded externally, no support is provided to specify a seed. Refer to the documentation linked above on seeding details.
RDRAND was introduced by Intel starting with the Ivy Bridge chipset so this will only work with these chips or newer. If you aren't sure about your hardware, the library build will tell whether it is supported or not.
Since native libraries are involved and the builds are not cross-platform, the utility is provided as source only for a Maven project including the librdrand source to be built locally.
Dependencies are minimal, sl4j and log4j for logging and junit and commons-math3 for testing.
Build requirements from a Java perspective are a JDK (1.7 if building unmodified) and Maven (developed and tested using Maven 3.0.4).
Makefiles and scripts for building librdrand and the JNI native code is included and the Maven build is configured to invoke them. The host on which the build is run must have gcc (min version 4.3.3), make and grep available. librdrand is built and linked into the native shared library generated using JNI, and referenced by the Java code.
NOTE: The source and target for the compiler plugin in the POM are set to 1.7, update this if necessary to the version of Java you are running (Java 5 or 6).
The project generates a single jar (excluding external dependencies) file which can be deployed and used by applications. The native shared library is included in the jar file from where it is extracted to the directory noted by the System property java.io.tmpdir and loaded dynamically at runtime.
No need for the System Administrator to deploy the native shared library to system library paths or register with ld.
Since the implementation extends java.util.Random it can be used transparently anywhere you would use it.
import java.util.Random;
import net.lizalab.util.RdRandRandom;
// ...
Random random = new RdRandRandom();Usage for the Uncommons Maths SeedGenerator is similarly straightforward:
import java.util.Random;
import net.lizalab.util.RdRandSeedGenerator
import org.uncommons.maths.random.AESCounterRNG;
// ...
Random random = new AESCounterRNG(new RdRandSeedGenerator());For the built-in randomness tests running on a headless server with:
- Intel Xeon E3-1275 V2 Ivy Bridge processor (3.5GHz)
- CentOS 6.3
- Oracle Server VM 1.7 (Default Settings)
RdRandRandom was consistently about 10 times faster than SecureRandom (running the default SHA algorithm and using /dev/random as the entropy source). Running the tests should allow you to verify this easily for your hardware.
The benefits in a high usage environment over default SecureRandom, given the supported bandwidth outlined by Intel and shown by the tests, should be obvious especially on headless servers.
A couple of basic tests of randomness are built-in to the project, Mean Test and Monte Carlo Pi Approximation test. Verify the successful completion of the tests before proceeding to use the utility.
Successful run of the Mean Test should display results like this:
-------------------------------------------------------
T E S T S
-------------------------------------------------------
Running net.lizalab.util.RdRandRandomTest
2013-09-13 19:38:54,743 [INFO ] net.lizalab.util.RdRandRandomTest - testRdRandRandom : Normal mean: 4.5
2013-09-13 19:38:54,743 [INFO ] net.lizalab.util.RdRandRandomTest - testRdRandRandom : Normal std: 3.0276503540974917
2013-09-13 19:38:54,743 [INFO ] net.lizalab.util.RdRandRandomTest - testRdRandRandom : Normal var: 9.166666666666666
2013-09-13 19:38:54,744 [INFO ] net.lizalab.util.RdRandRandomTest - testRdRandRandom : Generating 10000000 values.
2013-09-13 19:38:54,744 [INFO ] net.lizalab.util.RdRandRandomTest - testRdRandRandom : Sample mean expected in range 4.497127718676731 - 4.502872281323269 99.7% of the times.
2013-09-13 19:38:54,744 [INFO ] net.lizalab.util.RdRandRandomTest - testRdRandRandom : Sample mean expected in range 4.498085145784487 - 4.501914854215513 95% of the times.
.
.
2013-09-13 19:57:43,526 [INFO ] net.lizalab.util.RdRandRandomTest - meanTest : Time: 1971ms
2013-09-13 19:57:43,526 [INFO ] net.lizalab.util.RdRandRandomTest - meanTest : Distribution:
2013-09-13 19:57:43,527 [INFO ] net.lizalab.util.RdRandRandomTest - meanTest : 0: 999182
2013-09-13 19:57:43,527 [INFO ] net.lizalab.util.RdRandRandomTest - meanTest : 1: 999741
2013-09-13 19:57:43,527 [INFO ] net.lizalab.util.RdRandRandomTest - meanTest : 2: 1000009
2013-09-13 19:57:43,527 [INFO ] net.lizalab.util.RdRandRandomTest - meanTest : 3: 1000791
2013-09-13 19:57:43,527 [INFO ] net.lizalab.util.RdRandRandomTest - meanTest : 4: 999356
2013-09-13 19:57:43,527 [INFO ] net.lizalab.util.RdRandRandomTest - meanTest : 5: 1002547
2013-09-13 19:57:43,527 [INFO ] net.lizalab.util.RdRandRandomTest - meanTest : 6: 998484
2013-09-13 19:57:43,527 [INFO ] net.lizalab.util.RdRandRandomTest - meanTest : 7: 1000606
2013-09-13 19:57:43,527 [INFO ] net.lizalab.util.RdRandRandomTest - meanTest : 8: 1000099
2013-09-13 19:57:43,527 [INFO ] net.lizalab.util.RdRandRandomTest - meanTest : 9: 999185
2013-09-13 19:57:43,528 [INFO ] net.lizalab.util.RdRandRandomTest - meanTest : mean: 4.500089399999296, diff: 1.9866666510203067E-5
2013-09-13 19:57:43,528 [INFO ] net.lizalab.util.RdRandRandomTest - meanTest : sd: 2.8717184431423703
2013-09-13 19:57:43,528 [INFO ] net.lizalab.util.RdRandRandomTest - meanTest : var: 8.24676681668404Successful run of the Monte Carlo Pi Approximation Test should display results like this:
2013-09-13 19:39:11,703 [INFO ] net.lizalab.util.RdRandRandomTest - testRdRandRandomMonteCarloPiTest : Generating 1000000 points for Monte Carlo Pi Test. Expected precision: 3 digits, 3.14
.
.
2013-09-13 19:39:11,748 [INFO ] net.lizalab.util.RdRandRandomTest - testRdRandRandomMonteCarloPiTest : Running for RdRand..
2013-09-13 19:39:12,051 [INFO ] net.lizalab.util.RdRandRandomTest - monteCarloPiTest : Time: 303ms
2013-09-13 19:39:12,051 [INFO ] net.lizalab.util.RdRandRandomTest - monteCarloPiTest : Pi Approximation: 3.142456, Diff: 8.633464102070221E-4, Error %: 0.027481169757018142The tests are also run for java.util.Random and java.security.SecureRandom, however, unlike for net.lizalab.util.RdRandRandom, their tests results are not asserted, they are simply for reference.
RdRandRandom, the java.util.Random extension provided by this utility has been put through the Dieharder suite of tests, considered the best test suite out there currently for RNGs for research and cryptography, and has successfully passed it.
$ dieharder -l
#=============================================================================#
# dieharder version 3.31.1 Copyright 2003 Robert G. Brown #
#=============================================================================#
Installed dieharder tests:
Test Number Test Name Test Reliability
===============================================================================
-d 0 Diehard Birthdays Test Good
-d 1 Diehard OPERM5 Test Good
-d 2 Diehard 32x32 Binary Rank Test Good
-d 3 Diehard 6x8 Binary Rank Test Good
-d 4 Diehard Bitstream Test Good
-d 5 Diehard OPSO Suspect
-d 6 Diehard OQSO Test Suspect
-d 7 Diehard DNA Test Suspect
-d 8 Diehard Count the 1s (stream) Test Good
-d 9 Diehard Count the 1s Test (byte) Good
-d 10 Diehard Parking Lot Test Good
-d 11 Diehard Minimum Distance (2d Circle) Test Good
-d 12 Diehard 3d Sphere (Minimum Distance) Test Good
-d 13 Diehard Squeeze Test Good
-d 14 Diehard Sums Test Do Not Use
-d 15 Diehard Runs Test Good
-d 16 Diehard Craps Test Good
-d 17 Marsaglia and Tsang GCD Test Good
-d 100 STS Monobit Test Good
-d 101 STS Runs Test Good
-d 102 STS Serial Test (Generalized) Good
-d 200 RGB Bit Distribution Test Good
-d 201 RGB Generalized Minimum Distance Test Good
-d 202 RGB Permutations Test Good
-d 203 RGB Lagged Sum Test Good
-d 204 RGB Kolmogorov-Smirnov Test Test Good
-d 205 Byte Distribution Good
-d 206 DAB DCT Good
-d 207 DAB Fill Tree Test Good
-d 208 DAB Fill Tree 2 Test Good
-d 209 DAB Monobit 2 Test GoodThe test results and the code snippet used to facilitate the test are provided below. The latter can be used to run the tests independently.
$ java -cp ".:lizalab-rdrand-util-1.0.1.0.jar:slf4j-api-1.7.2.jar:slf4j-log4j12-1.7.2.jar:log4j-1.2.17.jar" RdRandRandomByteStream | dieharder -a -g 200
#=============================================================================#
# dieharder version 3.31.1 Copyright 2003 Robert G. Brown #
#=============================================================================#
rng_name |rands/second| Seed |
stdin_input_raw| 2.44e+07 | 977030350|
#=============================================================================#
test_name |ntup| tsamples |psamples| p-value |Assessment
#=============================================================================#
diehard_birthdays| 0| 100| 100|0.36411172| PASSED
diehard_operm5| 0| 1000000| 100|0.88369087| PASSED
diehard_rank_32x32| 0| 40000| 100|0.71750775| PASSED
diehard_rank_6x8| 0| 100000| 100|0.84716239| PASSED
diehard_bitstream| 0| 2097152| 100|0.78129829| PASSED
diehard_opso| 0| 2097152| 100|0.43713031| PASSED
diehard_oqso| 0| 2097152| 100|0.82525161| PASSED
diehard_dna| 0| 2097152| 100|0.07980804| PASSED
diehard_count_1s_str| 0| 256000| 100|0.14105319| PASSED
diehard_count_1s_byt| 0| 256000| 100|0.19181662| PASSED
diehard_parking_lot| 0| 12000| 100|0.51759383| PASSED
diehard_2dsphere| 2| 8000| 100|0.43073986| PASSED
diehard_3dsphere| 3| 4000| 100|0.71441897| PASSED
diehard_squeeze| 0| 100000| 100|0.07423913| PASSED
diehard_sums| 0| 100| 100|0.47308063| PASSED
diehard_runs| 0| 100000| 100|0.64974722| PASSED
diehard_runs| 0| 100000| 100|0.73524395| PASSED
diehard_craps| 0| 200000| 100|0.13334508| PASSED
diehard_craps| 0| 200000| 100|0.92114183| PASSED
marsaglia_tsang_gcd| 0| 10000000| 100|0.07463720| PASSED
marsaglia_tsang_gcd| 0| 10000000| 100|0.48134560| PASSED
sts_monobit| 1| 100000| 100|0.58809382| PASSED
sts_runs| 2| 100000| 100|0.34510658| PASSED
sts_serial| 1| 100000| 100|0.30344924| PASSED
sts_serial| 2| 100000| 100|0.20541369| PASSED
sts_serial| 3| 100000| 100|0.40854809| PASSED
sts_serial| 3| 100000| 100|0.47236232| PASSED
sts_serial| 4| 100000| 100|0.97359140| PASSED
sts_serial| 4| 100000| 100|0.44514849| PASSED
sts_serial| 5| 100000| 100|0.79162722| PASSED
sts_serial| 5| 100000| 100|0.42896763| PASSED
sts_serial| 6| 100000| 100|0.92300349| PASSED
sts_serial| 6| 100000| 100|0.86970826| PASSED
sts_serial| 7| 100000| 100|0.84263155| PASSED
sts_serial| 7| 100000| 100|0.68520161| PASSED
sts_serial| 8| 100000| 100|0.18243093| PASSED
sts_serial| 8| 100000| 100|0.03072194| PASSED
sts_serial| 9| 100000| 100|0.44281143| PASSED
sts_serial| 9| 100000| 100|0.83742799| PASSED
sts_serial| 10| 100000| 100|0.60364027| PASSED
sts_serial| 10| 100000| 100|0.36440095| PASSED
sts_serial| 11| 100000| 100|0.82346253| PASSED
sts_serial| 11| 100000| 100|0.88452367| PASSED
sts_serial| 12| 100000| 100|0.98997535| PASSED
sts_serial| 12| 100000| 100|0.88536579| PASSED
sts_serial| 13| 100000| 100|0.15217386| PASSED
sts_serial| 13| 100000| 100|0.72443691| PASSED
sts_serial| 14| 100000| 100|0.84832373| PASSED
sts_serial| 14| 100000| 100|0.88975306| PASSED
sts_serial| 15| 100000| 100|0.28587103| PASSED
sts_serial| 15| 100000| 100|0.13859319| PASSED
sts_serial| 16| 100000| 100|0.96573888| PASSED
sts_serial| 16| 100000| 100|0.51355422| PASSED
rgb_bitdist| 1| 100000| 100|0.26666100| PASSED
rgb_bitdist| 2| 100000| 100|0.99247247| PASSED
rgb_bitdist| 3| 100000| 100|0.99205147| PASSED
rgb_bitdist| 4| 100000| 100|0.94427180| PASSED
rgb_bitdist| 5| 100000| 100|0.41728892| PASSED
rgb_bitdist| 6| 100000| 100|0.00116208| WEAK
rgb_bitdist| 7| 100000| 100|0.25862202| PASSED
rgb_bitdist| 8| 100000| 100|0.55875428| PASSED
rgb_bitdist| 9| 100000| 100|0.25095178| PASSED
rgb_bitdist| 10| 100000| 100|0.94487328| PASSED
rgb_bitdist| 11| 100000| 100|0.78973737| PASSED
rgb_bitdist| 12| 100000| 100|0.69845271| PASSED
rgb_minimum_distance| 2| 10000| 1000|0.33817481| PASSED
rgb_minimum_distance| 3| 10000| 1000|0.06475846| PASSED
rgb_minimum_distance| 4| 10000| 1000|0.90024136| PASSED
rgb_minimum_distance| 5| 10000| 1000|0.01206348| PASSED
rgb_permutations| 2| 100000| 100|0.84085898| PASSED
rgb_permutations| 3| 100000| 100|0.81397567| PASSED
rgb_permutations| 4| 100000| 100|0.08274235| PASSED
rgb_permutations| 5| 100000| 100|0.25045381| PASSED
rgb_lagged_sum| 0| 1000000| 100|0.14567587| PASSED
rgb_lagged_sum| 1| 1000000| 100|0.91139281| PASSED
rgb_lagged_sum| 2| 1000000| 100|0.72974431| PASSED
rgb_lagged_sum| 3| 1000000| 100|0.38736451| PASSED
rgb_lagged_sum| 4| 1000000| 100|0.98807549| PASSED
rgb_lagged_sum| 5| 1000000| 100|0.79815846| PASSED
rgb_lagged_sum| 6| 1000000| 100|0.73861247| PASSED
rgb_lagged_sum| 7| 1000000| 100|0.36577571| PASSED
rgb_lagged_sum| 8| 1000000| 100|0.38560822| PASSED
rgb_lagged_sum| 9| 1000000| 100|0.06685343| PASSED
rgb_lagged_sum| 10| 1000000| 100|0.11253476| PASSED
rgb_lagged_sum| 11| 1000000| 100|0.05943949| PASSED
rgb_lagged_sum| 12| 1000000| 100|0.05578541| PASSED
rgb_lagged_sum| 13| 1000000| 100|0.76076261| PASSED
rgb_lagged_sum| 14| 1000000| 100|0.99452473| PASSED
rgb_lagged_sum| 15| 1000000| 100|0.13197216| PASSED
rgb_lagged_sum| 16| 1000000| 100|0.24799510| PASSED
rgb_lagged_sum| 17| 1000000| 100|0.99890408| WEAK
rgb_lagged_sum| 18| 1000000| 100|0.97884236| PASSED
rgb_lagged_sum| 19| 1000000| 100|0.08685069| PASSED
rgb_lagged_sum| 20| 1000000| 100|0.86653358| PASSED
rgb_lagged_sum| 21| 1000000| 100|0.44697224| PASSED
rgb_lagged_sum| 22| 1000000| 100|0.90474984| PASSED
rgb_lagged_sum| 23| 1000000| 100|0.79097716| PASSED
rgb_lagged_sum| 24| 1000000| 100|0.85425267| PASSED
rgb_lagged_sum| 25| 1000000| 100|0.79069951| PASSED
rgb_lagged_sum| 26| 1000000| 100|0.94148304| PASSED
rgb_lagged_sum| 27| 1000000| 100|0.82933818| PASSED
rgb_lagged_sum| 28| 1000000| 100|0.43473739| PASSED
rgb_lagged_sum| 29| 1000000| 100|0.74173963| PASSED
rgb_lagged_sum| 30| 1000000| 100|0.91688071| PASSED
rgb_lagged_sum| 31| 1000000| 100|0.21801685| PASSED
rgb_lagged_sum| 32| 1000000| 100|0.91977712| PASSED
rgb_kstest_test| 0| 10000| 1000|0.34091360| PASSED
dab_bytedistrib| 0| 51200000| 1|0.82690978| PASSED
dab_dct| 256| 50000| 1|0.12824228| PASSED
Preparing to run test 207. ntuple = 0
dab_filltree| 32| 15000000| 1|0.91449223| PASSED
dab_filltree| 32| 15000000| 1|0.70050593| PASSED
Preparing to run test 208. ntuple = 0
dab_filltree2| 0| 5000000| 1|0.99962726| WEAK
dab_filltree2| 1| 5000000| 1|0.37492397| PASSED
Preparing to run test 209. ntuple = 0
dab_monobit2| 12| 65000000| 1|0.85902180| PASSED $ java -cp ".:lizalab-rdrand-util-1.0.1.0.jar:slf4j-api-1.7.2.jar:slf4j-log4j12-1.7.2.jar:log4j-1.2.17.jar" RdRandRandomByteStream | dieharder -a -g 200 -m 10
#=============================================================================#
# dieharder version 3.31.1 Copyright 2003 Robert G. Brown #
#=============================================================================#
rng_name |rands/second| Seed |
stdin_input_raw| 4.65e+07 | 888358514|
#=============================================================================#
test_name |ntup| tsamples |psamples| p-value |Assessment
#=============================================================================#
diehard_birthdays| 0| 100| 1000|0.87386750| PASSED
diehard_operm5| 0| 1000000| 1000|0.62660880| PASSED
diehard_rank_32x32| 0| 40000| 1000|0.04168779| PASSED
diehard_rank_6x8| 0| 100000| 1000|0.97638394| PASSED
diehard_bitstream| 0| 2097152| 1000|0.05625039| PASSED
diehard_opso| 0| 2097152| 1000|0.56995244| PASSED
diehard_oqso| 0| 2097152| 1000|0.23630450| PASSED
diehard_dna| 0| 2097152| 1000|0.03606780| PASSED
diehard_count_1s_str| 0| 256000| 1000|0.05799853| PASSED
diehard_count_1s_byt| 0| 256000| 1000|0.43067541| PASSED
diehard_parking_lot| 0| 12000| 1000|0.10472999| PASSED
diehard_2dsphere| 2| 8000| 1000|0.88550088| PASSED
diehard_3dsphere| 3| 4000| 1000|0.99338887| PASSED
diehard_squeeze| 0| 100000| 1000|0.58098232| PASSED
diehard_sums| 0| 100| 1000|0.00000002| FAILED
diehard_runs| 0| 100000| 1000|0.58549842| PASSED
diehard_runs| 0| 100000| 1000|0.05140719| PASSED
diehard_craps| 0| 200000| 1000|0.89574614| PASSED
diehard_craps| 0| 200000| 1000|0.61781962| PASSED
marsaglia_tsang_gcd| 0| 10000000| 1000|0.07942143| PASSED
marsaglia_tsang_gcd| 0| 10000000| 1000|0.01525728| PASSED
sts_monobit| 1| 100000| 1000|0.71593252| PASSED
sts_runs| 2| 100000| 1000|0.12646554| PASSED
sts_serial| 1| 100000| 1000|0.79719169| PASSED
sts_serial| 2| 100000| 1000|0.77251784| PASSED
sts_serial| 3| 100000| 1000|0.66561832| PASSED
sts_serial| 3| 100000| 1000|0.11767838| PASSED
sts_serial| 4| 100000| 1000|0.94057906| PASSED
sts_serial| 4| 100000| 1000|0.64115787| PASSED
sts_serial| 5| 100000| 1000|0.56034921| PASSED
sts_serial| 5| 100000| 1000|0.44109159| PASSED
sts_serial| 6| 100000| 1000|0.38191552| PASSED
sts_serial| 6| 100000| 1000|0.58529672| PASSED
sts_serial| 7| 100000| 1000|0.49362195| PASSED
sts_serial| 7| 100000| 1000|0.36082916| PASSED
sts_serial| 8| 100000| 1000|0.81854736| PASSED
sts_serial| 8| 100000| 1000|0.96961365| PASSED
sts_serial| 9| 100000| 1000|0.98111802| PASSED
sts_serial| 9| 100000| 1000|0.36683143| PASSED
sts_serial| 10| 100000| 1000|0.44715344| PASSED
sts_serial| 10| 100000| 1000|0.42659613| PASSED
sts_serial| 11| 100000| 1000|0.12310022| PASSED
sts_serial| 11| 100000| 1000|0.45300647| PASSED
sts_serial| 12| 100000| 1000|0.03895779| PASSED
sts_serial| 12| 100000| 1000|0.24317614| PASSED
sts_serial| 13| 100000| 1000|0.21054381| PASSED
sts_serial| 13| 100000| 1000|0.87058684| PASSED
sts_serial| 14| 100000| 1000|0.06381627| PASSED
sts_serial| 14| 100000| 1000|0.41595994| PASSED
sts_serial| 15| 100000| 1000|0.91194072| PASSED
sts_serial| 15| 100000| 1000|0.71655000| PASSED
sts_serial| 16| 100000| 1000|0.45437075| PASSED
sts_serial| 16| 100000| 1000|0.44811188| PASSED
rgb_bitdist| 1| 100000| 1000|0.09351524| PASSED
rgb_bitdist| 2| 100000| 1000|0.42487109| PASSED
rgb_bitdist| 3| 100000| 1000|0.11919539| PASSED
rgb_bitdist| 4| 100000| 1000|0.94317403| PASSED
rgb_bitdist| 5| 100000| 1000|0.81957337| PASSED
rgb_bitdist| 6| 100000| 1000|0.73808098| PASSED
rgb_bitdist| 7| 100000| 1000|0.44632480| PASSED
rgb_bitdist| 8| 100000| 1000|0.99771137| WEAK
rgb_bitdist| 9| 100000| 1000|0.80671475| PASSED
rgb_bitdist| 10| 100000| 1000|0.69340937| PASSED
rgb_bitdist| 11| 100000| 1000|0.64178846| PASSED
rgb_bitdist| 12| 100000| 1000|0.48783457| PASSED
rgb_minimum_distance| 2| 10000| 10000|0.40662829| PASSED
rgb_minimum_distance| 3| 10000| 10000|0.56538655| PASSED
rgb_minimum_distance| 4| 10000| 10000|0.06432970| PASSED
rgb_minimum_distance| 5| 10000| 10000|0.15402124| PASSED
rgb_permutations| 2| 100000| 1000|0.74005516| PASSED
rgb_permutations| 3| 100000| 1000|0.95772253| PASSED
rgb_permutations| 4| 100000| 1000|0.26515691| PASSED
rgb_permutations| 5| 100000| 1000|0.06644306| PASSED
rgb_lagged_sum| 0| 1000000| 1000|0.38110382| PASSED
rgb_lagged_sum| 1| 1000000| 1000|0.96945747| PASSED
rgb_lagged_sum| 2| 1000000| 1000|0.05459364| PASSED
rgb_lagged_sum| 3| 1000000| 1000|0.09741920| PASSED
rgb_lagged_sum| 4| 1000000| 1000|0.97143688| PASSED
rgb_lagged_sum| 5| 1000000| 1000|0.31951837| PASSED
rgb_lagged_sum| 6| 1000000| 1000|0.99301824| PASSED
rgb_lagged_sum| 7| 1000000| 1000|0.44500945| PASSED
rgb_lagged_sum| 8| 1000000| 1000|0.39156958| PASSED
rgb_lagged_sum| 9| 1000000| 1000|0.51161200| PASSED
rgb_lagged_sum| 10| 1000000| 1000|0.95501539| PASSED
rgb_lagged_sum| 11| 1000000| 1000|0.30667257| PASSED
rgb_lagged_sum| 12| 1000000| 1000|0.78346664| PASSED
rgb_lagged_sum| 13| 1000000| 1000|0.90368944| PASSED
rgb_lagged_sum| 14| 1000000| 1000|0.90493840| PASSED
rgb_lagged_sum| 15| 1000000| 1000|0.23429415| PASSED
rgb_lagged_sum| 16| 1000000| 1000|0.36976045| PASSED
rgb_lagged_sum| 17| 1000000| 1000|0.01728072| PASSED
rgb_lagged_sum| 18| 1000000| 1000|0.91546611| PASSED
rgb_lagged_sum| 19| 1000000| 1000|0.79138582| PASSED
rgb_lagged_sum| 20| 1000000| 1000|0.87478973| PASSED
rgb_lagged_sum| 21| 1000000| 1000|0.92592114| PASSED
rgb_lagged_sum| 22| 1000000| 1000|0.91216185| PASSED
rgb_lagged_sum| 23| 1000000| 1000|0.94053990| PASSED
rgb_lagged_sum| 24| 1000000| 1000|0.64759065| PASSED
rgb_lagged_sum| 25| 1000000| 1000|0.90840442| PASSED
rgb_lagged_sum| 26| 1000000| 1000|0.31445527| PASSED
rgb_lagged_sum| 27| 1000000| 1000|0.91439647| PASSED
rgb_lagged_sum| 28| 1000000| 1000|0.54431309| PASSED
rgb_lagged_sum| 29| 1000000| 1000|0.95389466| PASSED
rgb_lagged_sum| 30| 1000000| 1000|0.71193616| PASSED
rgb_lagged_sum| 31| 1000000| 1000|0.72716614| PASSED
rgb_lagged_sum| 32| 1000000| 1000|0.22662076| PASSED
rgb_kstest_test| 0| 10000| 10000|0.00026752| WEAK
dab_bytedistrib| 0| 51200000| 10|0.74151942| PASSED
dab_dct| 256| 50000| 10|0.99535132| WEAK
Preparing to run test 207. ntuple = 0
dab_filltree| 32| 15000000| 10|0.13934018| PASSED
dab_filltree| 32| 15000000| 10|0.71655616| PASSED
Preparing to run test 208. ntuple = 0
dab_filltree2| 0| 5000000| 10|0.77329317| PASSED
dab_filltree2| 1| 5000000| 10|0.81542316| PASSED
Preparing to run test 209. ntuple = 0
dab_monobit2| 12| 65000000| 10|0.86973855| PASSEDThe one failed test is a defective test that fails at higher p sample levels of 1000 and above and is marked as do not use.
import java.io.IOException;
import java.util.Random;
import net.lizalab.util.RdRandRandom;
public class RdRandRandomByteStream {
public static void main(String[] args) throws IOException {
Random random = new RdRandRandom();
for (;;) {
byte[] num = new byte[4096];
random.nextBytes(num);
System.out.write(num);
}
}
}NOTE: The Java random byte stream needs to be terminated manually once the final test has completed since in its current incarnation it runs in an infinite for loop.
- Version 1.1 - Added Uncommons Maths SeedGenerator implementation to enable using RDRAND as seed source with UnCommons Maths RNGs.
- Version 1.0.1 - Fixed bug in mean test implementation in RdRandRandomTest where distributions array was not being reset between runs for different RNGs.
- Version 1.0 - Initial release of the utility providing an implementation of java.util.Random using RDRAND via JNI.