Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to Biren GPU Architecture
- Overview of Biren solutions and primary use cases.
- Detailed hardware layout, including cores, memory structures, and compute clusters.
- Comparative analysis with NVIDIA and AMD GPU architectures.
Establishing the Biren Programming Environment
- Installation procedures for the Biren SDK and runtime components.
- Understanding the underlying toolchain and compiler model.
- Exploring basic project structures and the build process.
GPU Programming with the Biren Stack
- Exploring thread and block organizational models.
- Managing memory efficiently and handling data transfers.
- Developing kernels and applying effective launch patterns.
Migrating from CUDA to Biren
- Techniques for translating existing CUDA codebases.
- Mapping common APIs and adapting to Biren’s specific structures.
- Guided labs and practice sessions for code conversion.
Debugging and Profiling Strategies
- Utilizing Biren’s specialized debugger and profiler tools.
- Systematically identifying performance bottlenecks.
- Analyzing memory access patterns and implementing optimizations.
Advanced Optimization Techniques
- Managing thread scheduling and instruction pipelining.
- Applying loop unrolling and leveraging shared memory effectively.
- Executing advanced kernel tuning to maximize throughput.
Case Studies and Real-World Applications
- Demonstrating model training using Biren accelerators.
- Practical examples of porting and profiling vision or NLP models.
- Evaluating performance metrics against CUDA/NVIDIA environments.
Summary and Recommended Next Steps
Requirements
- A solid understanding of GPU architecture and parallel processing concepts.
- Practical experience with CUDA, OpenCL, or comparable GPU programming environments.
- Familiarity with deep learning frameworks such as PyTorch or TensorFlow.
Target Audience
- HPC developers.
- AI infrastructure engineers.
- Specialists in performance optimization.
21 Hours
Testimonials (2)
The extensive selection of tools presented
Miruna Buzduga - Aeronamic Eastern Europe
Course - AI Enablement Training for Engineers
Step by step training with a lot of exercises. It was like a workshop and I am very glad about that.