Signaloid Announces Availability of Amazon AWS Machine Image (AMI) for Accelerating Compute Workloads Ranging from Finance to Reinforcement Learning

British computing technology company Signaloid announced the release of the Signaloid Compute Engine Amazon Machine Image (AMI) via AWS Marketplace. The release enables organizations to deploy Signaloid’s distribution-extended compute hardware (UxHw®) technology within their Amazon Virtual Private Clouds (VPCs).

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The AMI provides access to UxHw, which delivers orders-of-magnitude performance improvements on x86_64 and ARM AWS EC2 instances. Without requiring software rewrites, UxHw speeds up Monte Carlo methods in finance, AI, physics, engineering, and more.

The AMI provides access to UxHw, which delivers orders-of-magnitude performance improvements on x86_64 and ARM (AArch64) AWS Elastic Compute Cloud (EC2) instances. Without requiring software rewrites, UxHw enables existing applications to compute directly on probability distributions, automating algorithms such as Monte Carlo methods in finance and physics, importance sampling in reinforcement learning, and particle filters in physical AI and robotics. The technology works through binary translation and optimization at the LLVM intermediate representation (LLVM IR) level, with optional hardware acceleration via FPGAs and Signaloid’s C0-ASIC that was recently taped-out in an ultra-low-power TSMC process. Examples of performance achieved with the AMI include 430-fold speedup for Value at Risk (using geometric Brownian motion) and up to 580-fold speedup for Heath-Jarrow-Morton swaptions pricing.

For organizations who currently use AWS infrastructure and want to benefit from UxHw combined with the familiarity of AWS tools, the AMI permits rapid deployment to EC2/On-Premises compute instances to benefit from UxHw. Organizations also have the option to deploy applications to Signaloid’s managed compute infrastructure, which has ISO/IEC 27001:2022 certification and SOC 2 Type II attestation.

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