A High-Intensity Program for Performance Engineering Aspirants.
This is not a general-purpose coding bootcamp. This is a rigorous, 100-hour Advanced Specialization designed for students and graduates who want to master the low-level architectural secrets behind the AI revolution. We focus on “Performance Engineering”—where every millisecond counts.
📅 Batch Starts: June 8th
✅ Are You The Right Fit? (Self-Assessment)
To maintain the fast-paced nature of this specialization, we do not provide basic programming support. Ensure you meet the following before enrolling:
- Academic Background: Students of Degree / PG / Diploma / MCA / MSc (CS, AI/ML,IT, Data Science, ECE, or allied Engineering streams).
- Recent Graduates: Open to recent graduates (not currently in full-time professional roles).
- 🔴 Critical Prerequisite: You must be highly proficient in C Programming. You should already be comfortable with Pointers, Dynamic Memory Allocation (malloc/free), and Data Structures.
- Commitment: Can you dedicate 5 hours every day for 4 weeks? This hands-on programming program is high-intensity and moves rapidly. 80% attendance is mandatory for receiving the course completion certificate.
🎯 The Specialization Edge
- Beyond High-Level Coding: Move past Python/Java wrappers to write raw, high-performance kernels.
- 100-Hour Rigor: A deep-dive into hardware-aware programming that standard college curricula often skip.
- Professional Tooling: Direct exposure to industrial profilers and debuggers from Day 1 to visualize hardware execution.
- SIMT Mastery: Master the Single Instruction, Multiple Threads paradigm—the backbone of modern Supercomputing.
📚 Core Curriculum (Topics)
- Architectural Foundations: Decoding GPU vs. CPU execution flows and hardware-level parallelism.
- GPU Kernel Development in C: Implementation of massively parallel functions.
- The Memory Challenge: Strategic use of Global, Shared, and Constant memory to bypass hardware latency.
- Performance Analysis: Real-time visualization of hardware bottlenecks using industry-standard tools.
- Concurrency Engineering: Utilizing Streams to overlap compute and data movement.
- Modern Case Studies:
- Matrix Operations for Neural Network Acceleration.
- Real-time Image Processing Pipelines.
- High-Performance Computational Simulations.
🛠️ Industry Tools
Master the tools used by performance engineers to visualize, debug, and optimize code:
- NVIDIA® Nsight™ Systems: For system-wide performance analysis and visualizing CPU-GPU interactions.
- NVIDIA® Nsight™ Compute: For interactive kernel profiling and deep-dive hardware metric analysis.
- cuda-gdb: Professional-grade debugging for parallel threads.
- cuda-memcheck / Compute Sanitizer: For detecting memory leaks, misaligned accesses, and race conditions.
- NVCC Compiler: Mastering compilation flags for architecture-specific optimization.
🚀 Career Impact
- Niche Specialization: Transition from a “Generalist Developer” to a “Performance Engineer.”
- Hard-Tech Portfolio: Build a GitHub repository of optimized C kernels that prove your technical depth.
⏰ Intensive Structure (100 Hours)
- Live Online Technical Sessions: (2.5 Hours Daily) 09:30 AM – 10:45 AM & 2.00 PM – 3:15 PM (Monday to Friday for 4 weeks)
- Autonomous Lab Work: 2.5 Hours Daily (Mandatory self-study & deep practice).
⚠️ Hardware Requirement: Students must arrange their own GPU-enabled hardware or use cloud environments (e.g., Google Colab). GPU access is not provided by the organizers.
🎙️ About The Speaker
Dr. Mandar Gurav is a Parallel Programmer who enjoys helping people accelerate their applications on CPU and GPU platforms. He previously worked with Nvidia, Intel, Centre for Development of Advanced Computing (C-DAC) and MulticoreWare before founding Siddhivinayak Advanced Computing Labs Pvt Ltd. Over the last 16 years, he has delivered a number of CPU/GPU parallelization projects in the following domains – Atmospheric Modelling, Computational Fluid Dynamics, Circuit Simulation, Robotics, Haptics, Video processing. As a part of professional service, he is involved in conducting training programs, delivering sessions on his areas of expertise in government research laboratories, industry and educational institutes (IITs, NITs, Engineering Institutes etc).
He holds a PhD from Indian Institute of Technology Bombay (IITBombay) and Bachelor of Engineering (Computer Science and Engineering) from Walchand College of Engineering, Sangli.
💰 Inaugural Launch Offer
Special Batch Fee: ₹5,000/- only (Original Price: ₹10,000/-)
Early Bird Registration (on or before 3rd June): ₹4,000/- only
Note: This introductory pricing is subsidized to foster a community of high-performance developers. This program is only for students or recent graduates (not currently in full-time professional roles). Working Professionals are not allowed to enroll for this program.
Refund policy: If you don’t like the training for any reason, full refund available within 7 days from the start of the course, no questions asked.
⚠️ Enrollment Notice
Capacity: Limited Seats. First-come, first-served for those who meet the prerequisites.
Registration: https://rzp.io/rzp/ILOTyg1V
Contact: contact@svacl.com / 9373881607
Stop Writing Slow Code. Start Accelerating.
Note: This program utilizes the NVIDIA® CUDA™ platform. CUDA and NVIDIA are trademarks and/or registered trademarks of NVIDIA Corporation.