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AI & HPC Consultancy & Training
Consultancy • Training • Architecture

AI & HPC consultancy that turns compute into competitive advantage

Design, optimize and operate high-performance compute systems and ML pipelines — from strategy to production.

Consultancy Services

From strategy to implementation — solutions tailored to your workload and budget.

AI Strategy & Roadmap

Feasibility, data strategy, ROI modeling and prioritization for your AI initiatives.

HPC Architecture Design

Cluster sizing, GPU/CPU balance, storage and network design optimized for your workloads.

ML Pipeline Optimization

Accelerate training and inference workloads with our proven optimization methods.

Case Studies

Real-world implementations delivering measurable results.

Hybrid V100/A100 HPC Platform

Designed and implemented a cutting-edge hybrid GPU cluster combining NVIDIA V100 and A100 GPUs for diverse AI workloads.

  • 40% cost reduction through optimal GPU allocation
  • Unified platform for both training and inference
  • Automated workload scheduling across GPU types

Large Language Model Optimization

Optimized a 175B parameter LLM training pipeline reducing training time by 35%.

  • Improved GPU utilization from 65% to 89%
  • Reduced checkpointing overhead by 50%
  • Implemented efficient gradient accumulation

Training Programs

Hands-on courses for engineers, data scientists and ops teams.

BEGINNER

Intro to HPC & Parallel Programming

Learn fundamentals of high-performance computing and parallel programming paradigms.

Duration: 2 days Enquire Now →
INTERMEDIATE

Advanced AI Model Optimization

Techniques to optimize and deploy ML models for maximum performance.

Duration: 3 days Enquire Now →
ADVANCED

HPC Cluster Administration

Master cluster management, monitoring, and optimization techniques.

Duration: 5 days Enquire Now →

Daily HPC Learning Log

Short daily notes from my journey in High Performance Computing – tuning clusters, GPUs, schedulers, and AI workloads.

Day 1 – Benchmarking NCCL on A100

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.

February 5, 2026

Day 2 – Slurm QoS & Fair-Share 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.

February 6, 2026

Day 3 – Profiling PyTorch DDP at Scale

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.

February 7, 2026

Contact Us

Get in touch with our team for inquiries and consultations.

Saudi Arabia Office

📞 +966 559803072

📍 Riyadh, Saudi Arabia

India Office

📞 +91 9886622698

📍 Bengaluru, India