High-Performance Data & GPU Acceleration
Multi-GPU Data Acceleration Pipeline with RAPIDS & Polars
Accelerated complex data wrangling workloads by migrating CPU-bound Pandas/Polars operations to an enterprise GPU-accelerated environment.
Timeline: July 2025 – August 2025
Delivery: Production-Ready
✕ The Business & Technical Challenge
Large analytical computations were bottlenecked on single-threaded CPU architectures, causing hours of latency in data exploration and model preparation.
⚙ The Engineered Architecture & Solution
Architected and configured a high-throughput RAPIDS (cuDF/cuML) compute cluster leveraging Nvidia RTX 5090 GPUs on WSL with VS Code integration.
✓ Measured Business Outcome & Impact
Unlocked 10x+ computation speedups, reducing data preparation runtimes from hours to minutes.
Core Technology Stack
RAPIDScuDFPolarsPandasNvidia RTX 5090CUDAWSLVS Code
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