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In this paper, we propose ThundeRiNG, a resource-efficient andhigh-throughput system for generating multiple independent sequences of randomnumbers (MISRN) on FPGAs. Generating MISRN can be a time-consuming step in manyapplications such as numeric computation and approximate computing. Despitethat decades of studies on generating a single sequence of random numbers onFPGAs have achieved very high throughput and high quality of randomness,existing MISRN approaches either suffer from heavy resource consumption or failto achieve statistical independence among sequences. In contrast, ThundeRiNGresolves the dependence by using a resource-efficient decorrelator amongmultiple sequences, guaranteeing a high statistical quality of randomness.Moreover, ThundeRiNG develops a novel state sharing among a massive number ofpseudo-random number generator instances on FPGAs. The experimental resultsshow that ThundeRiNG successfully passes the widely used statistical test,TestU01, only consumes a constant number of DSPs (less than 1\% of the FPGAresource capacity) for generating any number of sequences, and achieves athroughput of 655 billion random numbers per second. Compared to thestate-of-the-art GPU library, ThundeRiNG demonstrates a $10.62\times$ speedupon MISRN and delivers up to $9.15\times$ performance and $26.63\times$ powerefficiency improvement on two applications ($\pi$ estimation and Monte Carlooption pricing). This work is open-sourced on Github athttps://github.com/Xtra-Computing/ThundeRiNG

ThundeRiNG: Generating Multiple Independent Random Number Sequences on FPGAs