Explore machine learning concepts related to memory. Clear explanations and practical insights.
Deep dive into CPU cache lines — interactive cache simulator with configurable associativity and replacement policies, false sharing MESI protocol visualization, access pattern benchmarks, and optimization techniques.
Explore the inner workings of RAM through beautiful animations and interactive visualizations. Understand memory cells, addressing, and the memory hierarchy.
High Bandwidth Memory (HBM) architecture: 3D-stacked DRAM with TSV technology powering NVIDIA GPUs and AI accelerators with TB/s bandwidth.
Complete guide to PyTorch pin_memory — how DMA transfers work, when pinning helps vs hurts, NUMA effects, profiling with torch.profiler, num_workers interaction, and debugging slow data loading.
Learn how memory controllers manage CPU-RAM data flow. Interactive demos of channels, ranks, banks, and command scheduling for optimal bandwidth.
Explore Linux memory management through interactive visualizations. Understand virtual memory, page tables, TLB, swapping, and memory allocation.
Master virtual memory and TLB address translation with interactive demos. Learn page tables, page faults, and memory management optimization.
Master sequential vs strided memory access patterns. Learn how cache efficiency and hardware prefetching affect application performance.
Discover how memory interleaving distributes addresses across banks for parallel access. Boost memory bandwidth in DDR5 and GPU systems.
Explore NUMA architecture and memory locality in multi-socket systems. Understand local vs remote memory access latency and optimization strategies.
Learn how Transparent Huge Pages (THP) reduces TLB misses by promoting 4KB to 2MB pages. Understand performance benefits and memory bloat tradeoffs.
Master Structure of Arrays (SoA) vs Array of Structures (AoS) data layouts for optimal cache efficiency, SIMD vectorization, and GPU memory coalescing.
Interactive visualization of LLM context windows - sliding windows, expanding contexts, and attention patterns that define model memory limits.