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Course Outline
Introduction to Biren GPU Architecture
- Overview of Biren technology and its primary use cases.
- Hardware configuration: cores, memory, and compute clusters.
- Comparative analysis with NVIDIA and AMD GPUs.
Configuring the Biren Programming Environment
- Installation of the Biren SDK and runtime components.
- Insights into the toolchain and compiler model.
- Foundational project structure and build workflows.
GPU Programming Using the Biren Stack
- Thread and block organizational models.
- Memory management strategies and data transfer mechanisms.
- Kernel development practices and launch patterns.
Migrating from CUDA to Biren
- Techniques for translating CUDA codebases.
- Mapping common APIs and necessary adaptations.
- Laboratory sessions focused on code conversion and practice.
Debugging and Profiling Methods
- Utilization of Biren’s native debugger and profiler tools.
- Strategies for identifying performance bottlenecks.
- Analysis of memory access patterns and subsequent optimization.
Advanced Optimization Techniques
- Thread scheduling mechanisms and instruction pipelining.
- Application of loop unrolling and shared memory utilization.
- Sophisticated kernel tuning to maximize throughput.
Case Studies and Practical Applications
- Model training procedures using Biren accelerators.
- Porting and profiling exercises for vision or NLP models.
- Performance benchmarking against CUDA/NVIDIA standards.
Summary and Future Directions
Requirements
- A solid grasp of GPU architecture and parallel processing concepts.
- Hands-on experience with CUDA, OpenCL, or comparable GPU programming frameworks.
- Proficiency 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.