GPU Memory Hierarchy & Optimization
Master GPU memory hierarchy from registers to global memory, understand coalescing patterns, bank conflicts, and optimization strategies for maximum performance
Explore machine learning concepts related to performance. Clear explanations and practical insights.
Master GPU memory hierarchy from registers to global memory, understand coalescing patterns, bank conflicts, and optimization strategies for maximum performance
Master filesystem mount options to control performance, security, and behavior. Explore common options, performance implications, and security hardening through interactive visualizations.
Comprehensive exploration of CPU pipeline stages, hazards, superscalar, and out-of-order execution
Performance optimization strategies and CPython optimizations
Master transparent filesystem compression with algorithms, compression ratios, and performance implications. Explore compression mechanisms through interactive visualizations.
Deep dive into the differences between green threads (user-space threads) and OS threads (kernel threads), with interactive visualizations showing scheduling, context switching, and performance implications.
Explore XFS - the high-performance 64-bit journaling filesystem optimized for large files and parallel I/O. Learn why it excels at handling massive data workloads.
Explore Flynn's Classification of computer architectures through interactive visualizations of SISD, SIMD, MISD, and MIMD systems.
Master hash tables through interactive visualizations of hash functions, collision resolution strategies, load factors, and performance characteristics.
Explore CPU pipeline stages, instruction-level parallelism, pipeline hazards, and branch prediction through interactive visualizations.
Master pipeline hazards through interactive visualizations of data dependencies, control hazards, structural conflicts, and advanced detection mechanisms.
Explore how CPU cache lines work, understand spatial locality, and see why memory access patterns dramatically impact performance through interactive visualizations.
Understand how different memory access patterns impact cache performance, prefetcher efficiency, and overall application speed through interactive visualizations.
Understand how memory interleaving distributes addresses across multiple banks to enable parallel access, dramatically improving memory bandwidth in modern systems from DDR5 to GPU memory.
Explore NUMA (Non-Uniform Memory Access) architecture, understanding how modern multi-socket systems manage memory locality and the performance implications of local vs remote memory access.
Deep dive into Transparent Huge Pages (THP), a Linux kernel feature that automatically promotes 4KB pages to 2MB huge pages. Learn how THP reduces TLB misses, page table overhead, and improves performance—plus the hidden costs of memory bloat and latency spikes.
Master Structure of Arrays (SoA) vs Array of Structures (AoS) data layouts for optimal cache efficiency, SIMD vectorization, and GPU memory coalescing with interactive visualizations.
Eliminating GPU initialization latency through nvidia-persistenced - a userspace daemon that maintains GPU driver state for optimal startup performance.
Understanding CPU cycles, memory hierarchy, cache optimization, and performance analysis techniques