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eTRNG Press Release

LSE TECHNOLOGIES ANNOUNCES eTrueRNG RANDOM NUMBER GENERATOR FOR LINUX

eTrueRNGTM algorithm provides high performance random number generation comparable to hardware true random number generators in quality.

For Immediate Release - Longmont, Colorado - LSE Technologies introduces its new eTrueRNG random number generation software providing effectively true random number generation for most applications. C object code modules allow developers of applications dependent on random numbers to easily incorporate a high quality random number generator (RNG) in their application.

“More and more types of software are utilizing random numbers and the quality of the output from the software is increasingly dependent on the quality of those random numbers.” explains Mike Lease, President and founder of LSE Technologies. “A wide range of applications from modeling and simulation to gaming to security rely on random numbers. For many of these applications the quality of the random numbers is critical but just as critical is the rate at which the random numbers are created. Most developers rely on the system random number generators that either produce notoriously poor random numbers or are notoriously slow in producing high quality random numbers.”

“We have developed a novel approach to random number generation based on a combination of proven approaches and innovative new concepts. Testing on data sets produced with our eTrueRNG algorithm shows results comparable to and even better than some highly respected hardware true RNGs. We achieved this by combining a number of pseudo-random number generators with a high quality deterministic number generator and real-time system entropy data. Our first product, the eTRNGTM C object code module for Linux not only achieves high levels of quality in its output numbers, it does so at over 50 Mbytes/second on a typical desktop computer.”

The eTRNG product is available in Basic and Advanced versions. Both versions feature:
  • Random and deterministic mode for applications that require repeatable sequences of random numbers.
  • “Turbo” mode that nearly doubles the number generation rate with only a slight decrease in output quality.
  • A variety of options to tailor the algorithm to the application’s requirements for randomness and performance.
The eTRNG Advanced version also provides multi-threaded operation and the real-time system entropy data option.

The Linux versions of eTRNG are available now in 32-bit and 64-bit versions. The Windows versions of eTRNG are planned for release in October 2016. The eTRNG pricing for research/academic use is $245 for the Basic version and $495 for the Advanced version. Additional information and test results are on the LSE Technologies website at www.lse-tech.com.



eTRNGTM is a trademark of LSE Technologies
Copyright 2016 LSE Technologies