Tensor Computing & GPU Execution Foundations

Matrix Multiplication (GEMM) Execution Mechanics

Tensor Layouts and Memory Ordering

SIMD vs SIMT Execution Models

Streaming Multiprocessor (SM) Architecture

CUDA Warp Scheduling and Divergence

Tensor Core Execution Systems

GPU Occupancy and Register Allocation

Arithmetic Intensity and Roofline Modeling

Compute-Bound vs Memory-Bound Workloads

Instruction-Level Parallelism in GPUs

PTX Assembly and SASS Fundamentals

Thread Block and Grid Synchronization

Asynchronous Compute and Overlapped Execution

Cooperative Groups and Distributed Shared Memory

GPU Hardware Generations (H100 → B200 → Future Architectures)