A process and system for producing random numbers by means of a quantum random number generator is disclosed, comprising the steps of operating a multimode laser in a laser cavity with periodic modulation of a net gain, and detecting the random intensity pattern produced by the inter-mode beating occurring within the laser cavity. The numbers produced are truly random and a minimal number of elements is required for operating the system.

A random number generation circuit may include a memory block. The random number generation circuit may include a fuse block configured to store an address of a failed memory cell from a memory cell array of the memory block, as a repair address, and generate a match signal by comparing the repair address with a normal address inputted from an exterior. The random number generation circuit may include a register configured to output a true random number by latching an address corresponding to activation timing of the match signal among normal addresses.

A method for generating a random number for use in a stochastic rounding operation is provided. The method includes executing an instruction that causes at least two operands to produce an intermediate result and incrementing a state of a random number generator. The method d further includes causing the random number generator to generate a random number in accordance with the state and producing a final result by utilizing the random number to determine a rounding of the intermediate result.

Embodiments include method, systems and computer program products for extracting entropy from mobile devices to generate random numbers. In some embodiments, first vibration data may be received from a first device. Second vibration data may be received from a second device. A first piece of entropy data may be generated using the first vibration data and a second piece of entropy data may be generated using the second vibration data. The first piece of entropy data and the second piece of entropy data may be aggregated. The first piece of entropy data and the second piece of entropy data may be stored in an entropy pool.

Embodiments include a random number generation entity having at least one switching cell comprising a pair of electrodes and a chalcogenide layer arranged between the pair of electrodes and a pulse generating entity coupled with the electrodes of the switching cell. The pulse generating entity is configured to provide an excitation pulse to the switching cell. The random number generation entity also includes a detection entity configured to provide a detection signal indicating whether an electrical property measured at the switching cell exceeds or falls below a threshold value due to applying the excitation pulse to the switching cell and a random number generation entity adapted to generate a random number based on the detection signal of the detection entity.

According to one embodiment, a permutation generator is described comprising a memory configured to store, for each number of a predetermined set of numbers, whether the number has already been included in a number sequence; a receiver configured to receive a random number; a determiner configured to select a number from those numbers of the set of numbers that have not yet been included in the number sequence as next element of the number sequence based on the random number and an output configured to output the selected number as the next element of the number sequence.

A process and system for producing random numbers by means of a quantum random number generator is disclosed, comprising the steps of operating a multimode laser in a laser cavity with periodic modulation of a net gain, and detecting the random intensity pattern produced by the inter-mode beating occurring within the laser cavity. The numbers produced are truly random and a minimal number of elements is required for operating the system.

A processor includes an execution unit to generate a random number. The execution unit includes entropy source circuits, correlation circuits, and an extractor circuit. The entropy source circuits include all-digital components and are to generate an initial randomized bit stream. The correlation circuits are to remove correlations from the initial randomized bit stream to yield an intermediate randomized bit stream. The extractor circuit is to select a subset of the intermediate randomized bit stream as a random output of the execution unit.

A semiconductor device includes a plurality of spin units individually including a memory cell configured to store values of spins in an Ising model, a memory cell configured to store an interaction coefficient from an adjacent spin that exerts an interaction on the spin, a memory cell configured to store an external magnetic field coefficient of the spin, and an interaction circuit configured to determine a subsequent state of the spin. The spin units individually include a random number generator configured to supply the random number to the plurality of the spin units and generate two-valued simulated coefficients of two values or simulated coefficients of three values in performing an interaction to determine a subsequent state of a spin of the spin units from a value of a spin from an adjacent spin unit, an interaction coefficient, and an external magnetic field coefficient.

A method for generating random numbers on multiprocessor systems and a multiprocessor system for generating true random numbers, using the method, generate truly random numbers with high entropy in a multiprocessor system with little additional effort to chip area and power dissipation. The method includes the steps of: measuring a phase error signal of a clock generator circuit of a first and a second processing unit respectively, forwarding the phase error signal of the respective clock generator circuit of the first and second processing unit to a true random network, combining the phase error signal of the clock generator circuit of the first processing unit and the phase error signal of the clock generator circuit of the second processing unit in the true random network to random bit streams, picking-up a random bit stream of the true random network, passing the respective random bit stream back to a random generator of the respective processing unit for outputting true random.