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Duration 21 hours
Course Outline
Overview of Biren GPU Architecture
- Introduction to Biren and its key use cases.
- Hardware configuration: cores, memory structure, and compute clusters.
- Benchmarking against NVIDIA and AMD GPU standards.
Configuring the Biren Development Environment
- Installing the Biren SDK and runtime components.
- Explaining the toolchain and compiler workflow.
- Establishing basic project structures and build procedures.
Developing GPU Code with the Biren Stack
- Detailed look at thread and block organization models.
- Managing memory allocation and data transfer operations.
- Creating kernels and defining launch patterns.
Migrating from CUDA to Biren
- Techniques for translating CUDA code to Biren syntax.
- Mapping common APIs and necessary adaptations.
- Practical labs for code conversion and practice.
Debugging and Performance Profiling
- Utilizing Biren’s integrated debugger and profiler tools.
- Pinpointing performance bottlenecks.
- Analyzing memory access patterns for optimization.
Advanced Optimization Strategies
- Managing thread scheduling and instruction pipelining.
- Applying loop unrolling and leveraging shared memory.
- Fine-tuning kernels for maximum throughput.
Real-World Case Studies and Examples
- Training models using Biren accelerators.
- Porting and profiling vision or NLP-based models.
- Performance comparison against CUDA/NVIDIA solutions.
Summary and Future Directions
Requirements
- A solid understanding of GPU architecture and parallel processing concepts.
- Prior experience working with CUDA, OpenCL, or comparable GPU programming frameworks.
- Familiarity with deep learning libraries such as PyTorch or TensorFlow.
Target Audience
- HPC developers.
- AI infrastructure engineers.
- Specialists in performance optimization.
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.
