HPC for Quant Trading Firms running backtesting at scale.
Credentials
We’ve spent years working together building large scale distributed systems that run on hundreds of thousands of machines and serve billions of users. Every time you leverage your network for a warm intro on LinkedIn, you use three databases that we’ve built: Venice, Liquid, and Espresso.
After LinkedIn, we were tech-leads of Ray, the leading open-source compute platform used by companies such as xAI, Cursor, Bridgewater, P72, Man Group, Two Sigma, and others. Ray has ~12M weekly downloads and is part of the PyTorch Foundation.
Product
https://www.youtube.com/watch?v=C6tl8Fr8t2I
We’re building large scale high performance computing (HPC) clusters for quantitative trading firms to run parallel simulation workloads such as backtesting.
The scale we’re targeting is
- 100 to 50,000 nodes of mixed hardware (CPUs and GPUs) on hyperscalers and neoclouds.
- up to 5,000,000 parallel tasks.
- spot instances for cheaper compute across multiple availability zones, hyperscalers, and neoclouds.
- < 50ms overhead for task dispatch and scheduling.
- run the compute in your cloud or on-prem environment to keep your alpha secure.
Our goal is to make testing trading strategies fast, cheap, and reliable.
Vision
We know that existing solutions do not handle this scale, do not have first-class support for spot-instances, and will not match our low-latency and high throughput performance.
Our technology generalizes to other large-scale compute workloads such as
- post-training and reinforcement learning (RL) for frontier and applied AI labs
- massively parallel robotics simulation and sim-to-real training for robot foundation model teams
- virtual screening and molecular dynamics for techbio and pharma R&D
- scientific simulation (CFD, climate, seismic, FEA) for HPC teams looking to move beyond MPI and SLURM.
Ask
Reach out if you
- Are running simulation workloads that require lots of computation at a quant trading firm.
- If you need HPC for a different use-case.
- Want to grab a beer and talk about distributed systems or HPC.
Cheers!
Ibrahim and Zac
