cache optimization

Scott Meyers explains how CPU caches work and why they matter for performance, covering cache levels, access speeds, associativity, and effects in multithreaded code. The focus is C++ and cache-aware, data-oriented programming.

Bryan Cantrill presents the ARC (Adaptive Replacement Cache) paper by Megiddo and Modha at Papers We Love. He opens with a survey of caching strategies before digging into the self-tuning LRU/MFU design.

Matt Kulukundis explains how Google designed SwissTable, a fast, cache-friendly hash table, step by step from std::unordered_map. The talk covers open addressing, SIMD probing and the tradeoffs of changing a fundamental data structure.

Casey Muratori's first refterm lecture lays out philosophies of optimization, distinguishing optimization from non-pessimization, which means avoiding needless work. It uses his fast terminal renderer project to show how fast computers really are.

Chandler Carruth's CppCon 2014 talk on writing fast C++, explaining why data structure choice and memory layout matter more than clever algorithms. It covers why standard containers like unordered_map perform poorly on modern CPUs.

Nicholas Ormrod's CppCon 2016 talk on how Facebook optimizes std::string with its open-source replacement fbstring. It covers storage layout tradeoffs, small string optimization and memory allocation behavior.

David Schachter describes how he made a data-collection Python program run 114,000 times faster, drawing on decades of experience. The talk covers pipelining, cache effects and other optimization lessons.

Matt Godbolt, creator of Compiler Explorer, tours surprising optimizations modern compilers perform, such as turning loops into closed-form sums and using popcount instructions. He explores what the compiler does behind the scenes.

Andrei Alexandrescu's ACCU 2016 talk previews material from his book on writing fast code, with a focus on optimization techniques such as sentinels and faster search.

The introductory lecture of Stephen Boyd's Stanford Convex Optimization I course (EE 364A). It outlines convex sets, functions and problems, and the course's coverage of least-squares, linear and semidefinite programming, duality and interior-point methods.

Kaze Emanuar explains how he rewrote and optimized the Super Mario 64 source code so it runs far faster on real N64 hardware. He covers performance bottlenecks and fixes in detail for his ROM hacks.

Optiver's Carl Cook explains how to build high-frequency trading systems in C++, where the critical path runs rarely but must be extremely fast. He covers techniques for low and predictable latency, including avoiding main memory and cache misses.

Chandler Carruth's CppNow 2013 keynote on how C++ builds complex software from simple emergent structures, and how compilers optimize them through inlining and value semantics.

Matthias Wandel tests old and new code on a range of PCs, including a new mini PC, to measure how much faster modern hardware really is. He also shows optimization techniques such as branchless code, with benchmark programs on GitHub.

Cliff Click walks through a small performance example on a modern out-of-order CPU. He covers pipelining, ILP, CISC vs RISC, multicore, and why cache misses and the memory subsystem dominate performance.

Kaze Emanuar searches for the best sine approximation for the Nintendo 64, comparing the lookup tables in Mario 64 and Ocarina of Time with polynomial alternatives. It walks through numerics and 3rd, 4th and 5th order approximations.

Matt Parker follows the community effort to speed up his slow Wordle-solving code, which ended up running hundreds of millions of times faster. He walks through the techniques contributors used.

Emery Berger explains why performance is hard to measure and deliver on modern hardware, showing how code layout and alignment can swamp optimization effects. He presents Stabilizer for statistically sound evaluation and Coz, a causal profiler.

Mike Acton of Insomniac Games argues that a program's purpose is transforming data, and shows how common C++ approaches work against that in performance-critical game development. He covers cache behavior, data layout and the limits of compilers.

Andrei Alexandrescu's CppCon 2019 talk revisits sorting, showing how branchless tricks, hybrid strategies and a cost metric can speed up std::sort-style algorithms on modern hardware.

Andrew Kelley, creator of Zig, presents practical data-oriented design techniques for shrinking memory footprint and making programs cache friendly. He ends with a case study of how these ideas sped up the Zig compiler.

Chandler Carruth's CppCon 2016 talk tries to defuse the heated debate over undefined behavior in C and C++. He explains from the compiler writer's perspective why UB exists and how it enables optimization.

Matt Godbolt builds a toy path tracer in C++ in three different styles and compares them on clarity, testability, compile time and run-time performance. The talk was given at CppCon 2019.

Chandler Carruth's CppCon 2016 talk on designing hybrid data structures for performance. He covers cache locality, working-set size and allocation overhead, and why standard C++ containers fall short.

Morphcat Games explains how they fit Micro Mages, a full-featured NES game, into 40 kilobytes. It covers compression of sprites and level layouts and other space-saving tricks.

Modern Vintage Gamer examines the claim from the Super Mario 64 decompilation project that the game shipped unoptimized, and puts it in the context of 1996 N64 development.

In Ars Technica's War Stories, Naughty Dog co-founder Andy Gavin explains how the team squeezed Crash Bandicoot onto the original PlayStation. They overwrote Sony library code in RAM, built custom animation compression, and streamed assets around slow seek times.

Casey Muratori shows how fast a terminal renderer can run, building a simple reference renderer that handles Unicode and colored text far quicker than Windows Terminal. He argues that common excuses for slow terminals do not hold up.

Casey Muratori's University of Twente guest lecture is a case study in how straightforward code can cut thousands of lines and tens of seconds of runtime down to a few dozen lines running in under a second. It uses concrete examples to show why software is often an order of magnitude slower than it should be.

Casey Muratori shows how typical 'clean code' object-oriented patterns can cost large factors in performance. He benchmarks them against simpler data-oriented code.

Andrew Adams, a Halide developer, presents the Halide language for image processing and tensor computation. The talk explains the separation of algorithm from schedule with illustrated examples of parallelism, locality and redundancy tradeoffs.

Jan Vitek of Northeastern University gives a meetup talk on the challenges of making the R language run fast. He explains what in R's semantics makes it hard to optimize and to build a JIT compiler for.

The winning demo from Revision 2015's oldskool competition, running on a real 1981 IBM PC with CGA at 4.77MHz. It uses extreme tricks to produce effects, graphics and sound far beyond what the hardware was thought capable of.

Gor Nishanov's CppCon 2018 talk on using tiny C++ coroutines to hide memory latency, interleaving useful work while prefetches bring cache lines in from main memory.

Emery Berger argues that performance is hard to measure and deliver on modern systems, showing how code layout and link order can swamp optimization effects. He presents tools that evaluate performance more reliably.

Matt Kulukundis reviews two years of Abseil's Swiss table hashtable, covering post-release optimizations, lessons from rolling it out across Google, design choices, and what global monitoring revealed.

Matt Godbolt's CppCon 2017 talk shows what modern compilers do with your C++ code, using Compiler Explorer to inspect generated assembly. It covers surprising optimizations and how the tool works.

A one-minute clip of slime mold placed on a map with food at the cities around Tokyo, growing a network that approximates the Tokyo-area railway system.

Armin Ronacher, creator of Flask, explains how CPython's internals and C API leak into the language's semantics. Using examples like the complexity of the add operation, he shows why Python is hard to optimize or reimplement.

Andrei Alexandrescu's CppCon 2015 talk argues that std::allocator is badly designed. He proposes building high-performance allocators from small composable, templated pieces.