LARGE-SCALE DATA ENGINE
Distributed Spark Fabric
RUNNING
$ spark-submit --master cluster --class SignalFabric.pipeline
dataset10.8 TB
rows1.42B
executors096
p95 latency18 ms
Stage 001 · scanning parquet partitions
0%
LARGE-SCALE NUMERICAL ENGINE
Adaptive Compute Graph
SOLVING
distributed solve
objective → constraints → convergence
high-dimensional data · sparse operators · numerical stability
SPARSE OPERATOR ACTIVITY
objective180.000
residual2.10e-4
stability99.4%
throughput8.2M/s
REAL-TIME MARKET INTELLIGENCE
Multi-Symbol Stream
STREAMING
symbols3,842
events / sec88,420
p95 latency14 ms
windows128
MICROSTRUCTURE HEATMAP
AI MODEL OPERATIONS CORE
Model Intelligence Fabric
DEPLOYING
ingest
→
train
→
validate
→
register
→
serve
→
monitor
AI
models scored840,000
inference / sec42,000
validation0.921
drift0.028
We are a 100% machine learning model-driven investment firm. We develop end-to-end models that ingest vast amounts of data each day, delivering robust, production-grade insights and truly accomplishing machine learning at scale. Our technology stack includes Spark clusters with thousands of cores and high-performance computing hardware that solve very large machine learning and nonlinear optimization problems in mere seconds.
About
Some of Our Current Infrastructure
| CPU Platform | Max Cores | Max Memory | Typical Role |
|---|---|---|---|
| AMD EPYC Zen 5 | 192 | 768 GB | Spark executors, ML training, HPC |
| AMD EPYC Zen 4 | 192 | 768 GB | Distributed compute |
| Intel Xeon 6 | 192 | 3 TB | SQL analytics, lakehouse, large JVM workloads |
| Intel Xeon Ice Lake | 64 | 1 TB | NVMe accelerated processing |
| AWS Graviton4 | 192 | 1.5 TB | ARM compute cluster |
| AWS Graviton3E | 64 | 128 GB | HPC simulation |
| GPU Platform | Memory | Architecture | Primary Workloads |
|---|---|---|---|
| NVIDIA H100 | 80 GB | Tensor Core | Foundation models |
| NVIDIA A100 | 40 / 80 GB | Tensor Core | Deep learning |
| NVIDIA L40S | 48 GB | RTX | Inference |
Machine Learning At Scale
Where We Are Located
Intelligent Machines Research Corporation is headquartered in Toronto’s financial district and develops advanced trading systems that combine machine learning, quantitative research, and robust infrastructure to deliver high-performance market solutions.