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MatLogica offers an award-winning toolkit that is 10x faster than PyTorch, JAX and TensorFlow, changing the landscape of complex model development. By automatically enabling the best possible performance for simulations, repetitive calculations, and the fastest automatic differentiation, it reduces architectural complexity, time-to-market for model development, yields orders of magnitude performance improvements, and drives substantial cloud cost savings.
A game-changing technology that has already helped our clients to achieve:
50% reduction in cloud costs
Over £12M in cloud computing savings per year
3x faster new model development
Up to 75% of modeling code base can be eliminted
30x faster on-demand simulations
New revenue streams accessed with faster intraday pricing & risk
10x more with your existing hardware
Improved operations and reduced risks
The MatLogica pioneered Code Generation AAD™ approach is the secret sauce that on-the-fly converts object-oriented code into bare-metal machine performance, designed for cross-platform execution. It is a toolkit that maximises developer productivity while enabling the best possible runtime performance.
Whether developing a new quant Library, or enhancing the existing codebase, MatLogica enables groundbreaking team efficiencies and model execution time!
MatLogica allows mix-mode execution across C++ and Python: for example, you can define custom payoffs in Python and send it to C++.
Live Risk
Example Use Case
Turn your batch-processing risk analytics into "always on" Live Risk server.
This example is based on Quantlib, supercharged by MatLogica AADC. Hit "Launch The Live Risk App" in the widget to see it live! You can access the code behind it using code examples on our website. You can read more about this using the link below.
Read nowHow to take your analytics to the next level?
In as little as 1 month, MatLogica will boost the performance of your simulations and enable Automatic Adjoint Differentiation.
Our custom-built JIT compiler enables AAD sensitivities to be computed faster than the original calculation!
The pioneering code generation AAD™ solution does not require extensive refactoring or introducing templates and comes with cutting-edge automated integration and debugging toolkits.
Our optimisation layer unlocks native CPU vectorisation (AVX2 and AVX512), safe multi-threading, and facilitates 6-100x speed-ups on a single core!
With our cross-platform execution, choose the hardware most suited for your workloads, with a flick of a switch.
If you're using CUDA you can enable AAD for your CUDA code with minimal changes and run on a CPU!
React to new market conditions faster by simplifying your modeling code base and accelerating prototyping and time-to-market.
Use your cloud resources more efficiently, and save up to 80% of cloud spend. Scale your compute quickly and securely using MatLogica Secure Binary Kernels.
Developers are more productive with the right tools
Focus on the models and delegate with confidence - our toolkit seamlessly handles performance optimisations and sensitivity computations, unlocking your full potential.
Quick & Easy
Integration
Integration
Simplified
Development
Development
Past
Initiative
Agnostic
Agnostic
Clean,
Intuitive
Interface
Interface
MatLogica’s toolkit offers a groundbreaking approach to enabling analytics acceleration, developer productivity and hardware efficiencies. Moreover, with its simple but effective tools, performance optimizations can be flexibly implemented and integrated.
MatLogica offers a unique AAD engine, bundled with a purposely developed just-in-time compiler, whereby banks can effortlessly optimize existing code with AAD, into machine code optimized for modern hardware. Because of this optimizing compiler, Matlogica's offering currently stands way above competition. I have seen the results and they are truly impressive.
One notable feature of AADC is that complex model calibration procedures do not require any special attention as is often the case with other AAD approaches. For example, we “AADC-record” simple Dupire volatility calculations, regression-based continuation value calibration and even Monte-Carlo based Cheyette model calibrations, with no special care needed to back- propagate adjoints. This has allowed us to eliminate a large amount of complex and hard to maintain code.
MatLogica offers a unique tool for developing machine learning applications in C++, C# or Python. It combines the simplicity of object-oriented design and the performance of graph-based languages. For applications like time series analysis, recursive neural nets, and similar, the performance of MatLogica AADC is impressive. Due to excellent vectorization and good support for multithreading, the execution on a CPU is very fast.