Meet Quside's Randomness Acceleration Platform Powered by Quside's Chip
Accelerate Now Your Results and Experiments in C++ and Python
At Quside, we use hardware-accelerated, high-throughput, highest-quality random number probability distribution generator technology to accelerate our customers' randomness-intensive workloads. Building on our proprietary phase-diffusion quantum random number generation technology, we created a data center-grade, ready-to-use solution as a PCIe accelerator card that provides random number probability distributions with high throughput and high quality.
Use our libraries to enable access to random number distributions, and obtain a speedup in your randomness-intensive workloads with minor changes in your design and development workflows, using our libraries for C++ and Python, together with series of examples and use cases, including Jupyter notebooks.
Speed-up Monte Carlo
Simulations up to 400%.
Speed-up scheduling and
and stock estimations.
Accelerate strategic and tactical
planning and forecasting.
Quside PCIe Randomness Acceleration cards
>> PCIe Gen2 x4, with up to 10 Gbps random distribution streams (32- and 64-bit floating-point, uniform and normal)
>> Leverage the whole computing power of your device by outsourcing the randomness generation subroutines
>> Using the highest seed quality, with up to 1 Gbps entropy rate
C++ and Python libraries to access the Randomness Acceleration
>> Get the highest speed-ups by integrating with the native C++ libraries
>> Get an instantaneous speed-up in your Python models using our adapted version of NumPy
>> Ready-to-use examples for C++, Python and Python Jupyter notebooks
>> Deploy the PCIe Randomness Acceleration Cards in a VMWare-virtualized standard server
>> Ready to use OVF (Open Virtualization Format) appliance with pre-installed libraries and dependencies, including examples and a Jupyter notebook environment
>> Full Randomness Acceleration Platform support
Stay tuned for further updates.
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