performance optimization

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.

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.

A Netflix performance engineer presents how Netflix tunes EC2 instances, covering instance type choice, Xen modes, SR-IOV and kernel tuning. The goal is near bare-metal performance in the cloud.

A Google Tech Talk on Yahoo's 14 rules for faster web pages and the YSlow tool. It covers front-end practices like avoiding @import and fixing ETags, with live analysis of popular sites.

Malte Skarupke's C++Now 2018 talk on hash table performance, explaining why std::unordered_map is slow and memory hungry and presenting faster designs, including his bytell hash map.

Emery Berger's CppCon 2020 plenary on why performance is hard on modern hardware after the end of Dennard scaling. It covers benchmarking pitfalls and introduces new profiling tools for finding real bottlenecks.

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.

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.

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.

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.

Netflix engineer Drew Gallatin's EuroBSDcon 2022 talk quantifies the older FreeBSD optimizations that let Netflix serve web traffic at 800Gb/s, including TSO, LRO, VM page cache zones, asynchronous sendfile and unmapped mbufs.

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.

Alex Russell's Chrome Dev Summit 2016 talk on building web experiences that work on slow, flaky networks and low-power devices. It argues developers should focus on the performance of real-world mobile hardware rather than desktop machines.

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.

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.

Chandler Carruth walks through tuning C++ performance, from writing benchmarks to analyzing results on real CPUs and compilers. It focuses on small-scale problems such as loop kernels, data structures and algorithms, and on keeping compilers from optimizing benchmarks away.

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.

A 2009 Google Tech Talk by Nicholas Zakas on the hidden performance pitfalls of JavaScript. It covers what is fast and slow in the language and how to avoid common bottlenecks.

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.

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.

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.

Charlie Marsh of Astral explains how uv, a Rust Python package manager, got so fast. He covers allocators, concurrency, zero-copy tricks and the challenges of Python packaging.

Aaron Hsu shows how to manipulate and transform tree data in APL using arrays and inverted tables instead of pointers. He claims much smaller code, better performance and easier parallelisation.

Leptos creator Greg Johnston examines Rust/WebAssembly frontend frameworks against JavaScript frameworks using the JS framework benchmark. He argues that WASM is no longer too slow for DOM-heavy rendering.

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.

Chandler Carruth shows how to squeeze more performance out of already-optimized C++ code, covering how the CPU executes it. The talk goes into pipelining, branch prediction and speculative execution using benchmarks.

Jack Moffitt presents the architecture of Servo, Mozilla's experimental browser engine written in Rust, focusing on parallelism across cores, GPUs and SIMD and the safety properties gained from Rust.

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.

Robert Collins explains why rustup installs were painfully slow on Windows and how changes to rustup and Windows cut install time from 3m30s to 14s. The talk covers NTFS, small files and the cost of antivirus hooks on file close.

A CppCon 2018 talk arguing that OOP has failed to deliver on reuse and performance, and presenting data-oriented design for C++ with practical worked examples from real systems.

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.

Aaron Patterson's RailsConf 2011 talk on Rails 3.1 performance, showing why deeper Rack middleware stacks slow Rails and how a shallower pipeline helps. It also touches on Rack API design.

Allan Jude of Klara presents work on making ZFS scale on fast NVMe storage, covering fixes to the TaskQueue interface and removal of bottlenecks. The talk was given at EuroBSDcon 2022 and describes raising write throughput from about 3 to over 7 GB/sec.

Ilya Grigorik of Google's Make the Web Fast team explains how to build a mobile site that appears on screen within one second. He covers the network and rendering constraints on mobile.

Richard Feldman explains how pure functional languages can match or beat imperative ones on performance. Compilers can turn immutable code into in-place mutation, avoiding naive copying. The talk draws on his work on the Roc language.

Cliff Click, author of HotSpot's JIT compiler, shares hard-won advice for people writing virtual machines at the VMSS16 workshop. Topics include interpreters, JITs and performance lessons.

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.

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.

A Google I/O 2013 talk by Android audio engineers on why reliable, low-latency audio is hard on the platform. It covers problem areas across the stack, platform work underway and techniques apps can use.

Alexis King's ZuriHac 2020 talk on how effect systems in Haskell can be implemented efficiently. It looks at the performance cost of effect libraries and how to reduce it.