Design, optimize and operate high-performance compute systems and ML pipelines — from strategy to production.
High Performance Computing
From strategy to implementation — solutions tailored to your workload and budget.
Feasibility, data strategy, ROI modeling and prioritization for your AI initiatives.
Cluster sizing, GPU/CPU balance, storage and network design optimized for your workloads.
Accelerate training and inference workloads with our proven optimization methods.
Real-world implementations delivering measurable results.
Designed and implemented a cutting-edge hybrid GPU cluster combining NVIDIA V100 and A100 GPUs for diverse AI workloads.
Optimized a 175B parameter LLM training pipeline reducing training time by 35%.
Hands-on courses for engineers, data scientists and ops teams.
Learn fundamentals of high-performance computing and parallel programming paradigms.
Techniques to optimize and deploy ML models for maximum performance.
Master cluster management, monitoring, and optimization techniques.
Short daily notes from my journey in High Performance Computing – tuning clusters, GPUs, schedulers, and AI workloads.
Tested NCCL all-reduce performance across 4×A100 GPUs with different message sizes and learned how bandwidth vs latency dominates at different regimes. Captured baselines for future Slurm topology tuning.
Experimented with Slurm fair-share and QoS configuration to prioritize long-running AI training jobs while keeping short interactive jobs responsive. Verified impact using sacct and sshare.
Used PyTorch profiler and Nsight Systems to identify communication bottlenecks in DDP runs. Compared gradient bucketing strategies and observed impact on overlap between compute and communication.
Get in touch with our team for inquiries and consultations.
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📍 Riyadh, Saudi Arabia
📞 +91 9886622698
📍 Bengaluru, India