Chapter 12. Tensor and Matrix Acceleration
Section 1. Matrix Multiplication Fundamentals
- GEMM operation principles
- Blocking and tiling strategies
- Data reuse optimization
- Arithmetic intensity considerations
Section 2. Tensor Core Architecture
- Systolic array organization
- Matrix multiply-accumulate units
- Dataflow and accumulation patterns
- Precision and throughput balance
Section 3. Mixed Precision Support
- FP16, BF16, TF32 computation
- INT8 and INT4 quantization
- Accumulator precision control
- Conversion and normalization units
Section 4. Tensor Memory Layout
- Row-major and column-major ordering
- Tiled and blocked formats
- Swizzling for conflict avoidance
- Efficient memory access patterns
Section 5. Sparse Matrix Acceleration
- CSR and COO representations
- Structured sparsity (2:4, 4:8)
- Zero-skipping hardware logic
- Compression and decompression paths
Section 6. Verilog Implementation
- Systolic array module
- Matrix multiply-accumulate block
- Data distribution network
- Tensor core testbench
Chapter 13. Ray Tracing Hardware
Section 1. Ray Tracing Fundamentals
- Ray representation
- Intersection with primitives
- BVH construction principles
- Traversal algorithms
Section 2. RT Core Architecture
- Ray-box intersection logic
- Ray-triangle intersection unit
- BVH traversal engine
- Hit and miss determination
Section 3. Acceleration Structures
- BVH node hierarchy
- Memory layout optimization
- Update and refit mechanisms
- Build-time vs runtime tradeoffs
Section 4. Ray Coherence and Sorting
- Coherent ray batching
- Ray binning and bucketing
- Cache-aware reordering
- Wavefront path tracing
Section 5. Integration with Rasterization
- Hybrid rendering pipeline
- Shader-based ray generation
- Shader binding table
- Payload management
Section 6. Verilog Implementation
- Ray-box intersection module
- Ray-triangle intersection unit
- BVH traversal FSM
- RT core testbench
Chapter 14. Synchronization and Memory Ordering
Section 1. Memory Consistency Models
- Sequential and relaxed models
- Acquire-release semantics
- Visibility scopes
- GPU-specific ordering rules
Section 2. Barriers and Fences
- Block and grid-level barriers
- Memory fence types
- System-wide synchronization
- Performance overhead
Section 3. Cache Coherence
- Write-invalidate protocols
- Directory-based coherence
- Cross-core consistency
- Heterogeneous CPU-GPU models
Section 4. Atomic Operations
- Read-modify-write logic
- Compare-and-swap
- Arbitration circuits
- Performance optimizations
Section 5. Lock-Free Algorithms
- Wait-free synchronization
- ABA problem handling
- Lock-free queues
- GPU-specific design considerations
Section 6. Verilog Implementation
- Barrier synchronization module
- Atomic operation unit
- Memory fence controller
- Synchronization testbench
Chapter 15. Advanced Rendering Features
Section 1. Tessellation Pipeline
- Hull shader and control points
- Fixed-function tessellator
- Domain shader operations
- Adaptive tessellation control
Section 2. Geometry Processing
- Geometry shader stage
- Primitive amplification
- Stream output
- Layered rendering
Section 3. Mesh Shaders
- Meshlet-based processing
- Task and mesh shader stages
- Workgroup culling and amplification
- Hardware resource mapping
Section 4. Variable Rate Shading
- Shading rate images
- Coarse shading patterns
- Foveated rendering
- Performance and power gains
Section 5. Deferred Rendering Architecture
- G-buffer composition
- Geometry and lighting passes
- Tile-based deferred shading
- Bandwidth and efficiency analysis
Section 6. Verilog Implementation
- Tessellator hardware
- Meshlet processor
- VRS controller
- G-buffer manager testbench
Chapter 16. Display and Video Engines
Section 1. Display Controller
- Timing generation (HSYNC and VSYNC)
- Frame buffer scanning
- Pixel pipeline organization
- Multi-display management
Section 2. Display Compression
- Display Stream Compression (DSC)
- Encoder and decoder design
- Bandwidth reduction analysis
- Visual quality metrics
Section 3. Video Decode Acceleration
- H.264, H.265, VP9, and AV1 decoding
- Bitstream parsing and entropy decoding
- Motion compensation hardware
- Parallel decode engines
Section 4. Video Encode Acceleration
- Motion estimation logic
- Rate control mechanisms
- Entropy encoder design
- Multi-format support
Section 5. Video Processing Pipeline
- Scaling and filtering
- Color space conversion
- Deinterlacing and denoising
- HDR tone mapping
Section 6. Verilog Implementation
- Display timing generator
- Video decoder FSM
- Motion estimation module
- Video pipeline testbench
Chapter 17. Interconnect and Communication
Section 1. On-Chip Networks
- Mesh and crossbar topologies
- Router architecture and buffering
- Flow control and arbitration
- Deadlock prevention
Section 2. Memory Crossbar
- SM-to-memory partition links
- Bandwidth scheduling
- Virtual channels
- QoS enforcement
Section 3. PCIe Interface
- Protocol layer overview
- DMA engine design
- Peer-to-peer communication
- Error handling
Section 4. High-Speed Serial Links
- NVLink and Infinity Fabric
- CXL and coherent interfaces
- PHY design and equalization
- Latency and throughput tuning
Section 5. Multi-GPU Communication
- GPU-to-GPU transfers
- Collective operations
- Topology optimization
- Scalability challenges
Section 6. Verilog Implementation
- Crossbar switch module
- Round-robin arbiter
- PCIe transaction engine
- NoC router and testbench
Chapter 18. Performance Analysis and Optimization
Section 1. Performance Metrics
- Throughput (GFLOPS and TFLOPS)
- Bandwidth utilization
- Cache efficiency
- Power and thermal metrics
Section 2. Bottleneck Identification
- Memory-bound and compute-bound workloads
- Latency versus bandwidth limits
- Roofline analysis
- Profiling methodology
Section 3. Performance Counters
- Counter and sampler architecture
- Multiplexing techniques
- Key hardware metrics
- PMU software interfaces
Section 4. Workload Characterization
- Instruction mix and balance
- Cache and memory patterns
- Thread divergence statistics
- Power behavior profiling
Section 5. Optimization Techniques
- Occupancy tuning
- Coalesced memory access
- Shared memory utilization
- Instruction scheduling
Section 6. Power and Thermal Management
- Dynamic power reduction
- Workload-based DVFS
- Thermal throttling
- Efficiency optimization
Chapter 19. Physical Design and Manufacturing
Section 1. Floorplanning
- Die partitioning and hierarchy
- Block placement and routing
- Power grid and clock tree
- Thermal optimization
Section 2. Synthesis and Timing Closure
- RTL synthesis flow
- Timing constraints and setup
- Clock domain verification
- Multi-mode optimization
Section 3. Place and Route
- Placement algorithms
- Routing congestion management
- Signal integrity checks
- IR drop and EM control
Section 4. Design for Test
- Scan insertion
- Built-in self-test
- JTAG and boundary scan
- Yield analysis
Section 5. Packaging Technologies
- Flip-chip and BGA packaging
- Thermal interface materials
- Multi-chip modules
- TSV-based stacking
Section 6. Advanced Integration
- Chiplet architectures
- Die-to-die interconnects
- UCIe protocol
- Heterogeneous integration
Chapter 20. Future Directions and Emerging Technologies
Section 1. Modern GPU Case Studies
- NVIDIA Hopper and AMD RDNA3
- Intel Arc and Apple GPU designs
- Mobile GPUs (Mali, Adreno)
- Design tradeoff comparisons
Section 2. Specialized AI Accelerators
- Google TPU and Cerebras engine
- Graphcore IPU and Groq LPU
- Comparison with general GPUs
- Domain-specific optimization
Section 3. Beyond Moore’s Law
- Process scaling limits
- GAA and CFET transistor evolution
- Advanced packaging methods
- Economic and design impact
Section 4. Emerging Memory Technologies
- HBM4 and next-gen DRAM
- Processing-in-memory concepts
- Persistent and near-data memory
- Memory-centric system design
Section 5. Novel Computing Paradigms
- Neuromorphic and optical computing
- Quantum-accelerated systems
- Approximate computation
- Stochastic and hybrid models
Section 6. Sustainability and Green Computing
- Power efficiency trends
- Carbon footprint reduction
- Lifecycle optimization
- Renewable-powered data centers
Section 7. Research Frontiers
- AI-driven hardware design
- Self-optimizing microarchitectures
- Secure and open GPU initiatives
- Future scalability challenges