Real World Go Andrew Gerrand May 9, 2011 Background 3 Google Confidential Why Go? • Statically typed languages are efficient, but typically bureaucratic and overly complex. • Dynamic languages can graphics and sound, – network tools, – and much more. • Now we call Go a “general-purpose language.” Real World Go 4 Google Confidential Heroku • http://www.heroku.com/ • Heroku provides cloud hosting add the web viewer on his train ride home and without requiring external dependencies. This is a real testament to how well Go mixes systems and application programming." Mechanical source formatting

Real world Rust Why and how we use Rust in TiKV 黄东旭 PingCAP 关于我 ● 黄东旭 Dongxu_Huang ● Open source hacker / Infrastructure Engineer ● MSRA / Netease / Wandoujia / PingCAP ● CTO of PingCAP ● Codis

using a wave digital voltage source, resistor, and capacitor, all connected with a series adaptor. Real-Time Circuit Simulation with Wave Digital Filters in C++ Author: Jatin Chowdhury Affiliation: Chowdhury part of their sound-processing algorithms. Given that audio effects are typically required to run in “real-time”, traditional circuit modelling softwares (e.g. LTSpice) are typically not suitable for this Filters, allowing the user to quickly and easily construct circuit simulations that are suitable for real-time applications. Wave Digital Filters Wave Variables Wave Digital Filters (WDFs) use “wave variables”

Real-Time Unified Data Layers: A New Era for Scalable Analytics, Search, and AI v 1.1Table of Contents Introduction 1. The Interconnection of Analytics, Search, and AI 2. What is a Real-Time Unified Unified Data Layer? 3. Why Do You Need a Real-Time Unified Data Layer? 4. 5.CrateDB: A Modern Real-Time Unified Data Layer1. Introduction Data teams are facing more challenges than ever. As applications data engineering and architecture teams must design systems that not only scale but also deliver real-time access and insights. However, the complexity isn’t just technical—business expectations have

iZotope Inc.iZotope real-time audio plug-ins | music, film, television, and radio iZotope Inc.iZotope real-time audio plug-ins | music, film, television, and radio iZotope Inc.iZotope real-time audio plug-ins plug-ins | music, film, television, and radio iZotope Inc.iZotope real-time audio plug-ins | music, film, television, and radio iZotope Inc.Glass Properties Making a legacy run-time system compile-time model - Hosts can call us from any thread - Each host may do this this differently Challenges for real-time audio plug-ins Confidential property of iZotope Inc.Canvas (ca. 2002)JUCE (ca. 2004) Canvas

LLVM’s Real-time Safety Revolution Tools for Modern Mission Critical SystemsChris Apple ● 10-year veteran of the audio industry ● Previously Dolby, Roblox, Spatial Inc. ● Currently: layabout David performance constraintsAgenda 1. Real-time programming 2. Existing strategies 3. RealtimeSanitizer 4. Performance constraints 5. Comparing and contrasting 50% 50%Agenda 1. Real-time programming 2. Existing “deadlines".1. Provide the right answer… 2. … in the right time.Missed deadlines Real-time programmingReal-time code in C++ Real-time programmingvoid process (float * audio) { // You have 11.6 ms from

There are three specified standard floating-point values that do not correspond to any point on the real number line: For further discussion of how these non-finite floating-point values are ordered with typemax(Float32)) (-Inf32, Inf32) julia> (typemin(Float64),typemax(Float64)) (-Inf, Inf) Machine epsilon Most real numbers cannot be represented exactly with floating-point numbers, and so for many purposes it is larger for larger values. In other words, the representable floating-point numbers are densest in the real number line near zero, and grow sparser exponentially as one moves farther away from zero. By definition

There are three specified standard floating-point values that do not correspond to any point on the real number line: For further discussion of how these non-finite floating-point values are ordered with typemax(Float32)) (-Inf32, Inf32) julia> (typemin(Float64),typemax(Float64)) (-Inf, Inf) Machine epsilon Most real numbers cannot be represented exactly with floating-point numbers, and so for many purposes it is larger for larger values. In other words, the representable floating-point numbers are densest in the real number line near zero, and grow sparser exponentially as one moves farther away from zero. By definition

There are three specified standard floating-point values that do not correspond to any point on the real number line: Float16 Float32 Float64 Name Description Inf16 Inf32 Inf positive infinity a value typemax(Float32)) (-Inf32, Inf32) julia> (typemin(Float64),typemax(Float64)) (-Inf, Inf) Machine epsilon Most real numbers cannot be represented exactly with floating-point numbers, and so for many purposes it is larger for larger values. In other words, the representable floating-point numbers are densest in the real number line near zero, and grow sparser exponentially as one moves farther away from zero. By definition

There are three specified standard floating-point values that do not correspond to any point on the real number line: Float16 Float32 Float64 Name Description Inf16 Inf32 Inf positive infinity a value typemax(Float32)) (-Inf32, Inf32) julia> (typemin(Float64),typemax(Float64)) (-Inf, Inf) Machine epsilon Most real numbers cannot be represented exactly with floating-point numbers, and so for many purposes it is larger for larger values. In other words, the representable floating-point numbers are densest in the real number line near zero, and grow sparser exponentially as one moves farther away from zero. By definition