High accuracy filtering and pattern matching at 1000x speed for reduced time to strategy.
Increase the speed and accuracy of quantitative analysis and backtesting with high throughput linear algebra and machine learning models.
Fewer false positives using more advanced models, in real-time, with extremely low latency at high throughput.
See our technology solutions in action for some of the most common financial service models.
Groq will be at the following industry-leading events. If you are attending, reach out and schedule a time to meet.
STAC events bring together CTOs and other industry leaders responsible for solution architecture, infrastructure engineering, application development, machine learning/deep learning engineering, data engineering, and operational intelligence to discuss important technical challenges in trading and investment.
The International Conference for High-Performance Computing, Networking, Storage, and Analysis.
The AI Summit New York is the only event in North America dedicated to the scalable implementation of AI for business with discernible and actionable takeaways for your organization.
The revolutionary, fully deterministic GroqChip processor is the core of scalable performance. Built from the ground up to accelerate AI, ML, and HPC workloads, GroqChip was designed to reduce data movement for predictable low-latency performance, bottleneck-free. Featuring 16 chip-to-chip interconnects and 230MB of SRAM, this standalone chip provides flexible integration into embedded applications.
For large scale deployments, GroqNode server provides a rack-ready scalable compute system. The eight GroqCard™ set features integrated chip-to-chip connections alongside dual server-class CPUs and up to 1TB of DRAM in a 4U server chassis, GroqNode is built to enable high performance and low latency deployment of large deep learning models.
For data center deployments, GroqRack provides an extensible accelerator network. Combining the power of an eight GroqNode™ set, GroqRack features up to 64 interconnected chips. The result is a deterministic network with an end-to-end latency of only 1.6µs for a single rack, ideal for massive workloads and designed to scale out to an entire data center.