virtual machine

Dan Bornstein's Google I/O 2008 talk on the internals of Dalvik, the virtual machine that runs Android code. It covers the motivation for its design, the dex format and its register-based interpreter, plus tips for writing code that suits the platform.

A talk by Yuri Iozzelli at a WebAssembly meetup on CheerpX, an x86 virtual machine running in the browser. It uses a JIT compiler that emits WebAssembly at runtime to run real native applications. It covers the architecture and demos such as porting a multiplayer C++ game.

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.

Chris Lattner and Brennan Saeta present Swift for TensorFlow at the TensorFlow Dev Summit 2019, covering language-integrated automatic differentiation and tooling for machine learning in Swift.

Pete Hunt explains why React's virtual DOM was built, how it compares with databinding-style systems, and what it means for future browser technology. Recorded at FutureJS 2014 in Barcelona.

Tom Dale explains the internals of the Glimmer VM, Ember's rendering engine, which compiles templates to opcodes. The talk includes a performance benchmark demo.

A Curry On talk by Lars Bak, known for V8 and Dart, on building a secure and robust IoT development platform. It discusses language and VM design choices for small devices.

Brian Karis's SIGGRAPH 2021 talk explains how Unreal Engine 5's Nanite virtualized geometry works. It covers mesh import, the data structures, streaming, decompression, culling, software and hardware rasterization, and shading.

In this 2019 GDC talk, Alex Schwartz and Ziba Scott explain how they flooded the app stores with over 1,500 auto-generated slot machine games to find the lowest bar for success. They tour the dark side of the mobile app market.

A QCon London 2020 talk by Tesla engineers on the architecture of Tesla's Virtual Power Plant. It covers aggregating distributed batteries and solar with vertically integrated hardware and software across cloud and edge.

Hans Rosling makes the case that the washing machine was the greatest invention of the industrial revolution. Using Gapminder graphics, he shows how electricity and economic growth free up time for reading and learning.

Ali Rahimi accepts the NIPS 2017 Test of Time Award and argues that machine learning has become alchemy, with practice running ahead of understanding.

David Beazley's PyCon India closing keynote, in which he live-codes a stack machine and grows it into an interpreter that runs WebAssembly, then uses it to play a Rust-written game. It requires no prior WebAssembly knowledge.

Rob Pike shows how the Go text/template lexer is built, using state functions, goroutines and channels. The talk was given at a Google Technology User Group in Sydney in 2011.

Tom7 explains how he built a SIGBOVIK 2017 paper made only of printable ASCII bytes that is also a valid DOS executable. He writes a C compiler targeting printable x86 without self-modifying code and solves the puzzles the constraint creates.

Geoffrey Hinton's Google Tech Talk linking machine learning to biology, explaining dropout as a form of model averaging and why sexual reproduction and stochastic spiking neurons may prevent overfitting.

Bryan Cantrill of Oxide Computer Company gives a Stanford EE380 talk on rethinking the server. He argues that hyperscaler-style rack-scale machines with open firmware, RISC-V and Rust should be available to everyone, not just the giants.

Bryan Cantrill's Velocity NYC 2015 talk argues for running containers directly on bare metal rather than layering them on virtual machines. He covers the history of containers and how SmartOS runs Linux workloads via syscall emulation.

Peter Norvig's 2007 Google talk on theorizing from data, covering what huge datasets can do for language understanding, translation, information extraction and inference. It argues that more data often beats cleverer models.

Micah Lee's Circle of HOPE 2018 talk on Qubes OS, which isolates activities in separate virtual machines so one compromise, such as a bad PDF or USB stick, does not expose everything. He gives an overview timed around the Qubes 4.0 release.

Kalman Reti, one of the last Symbolics developers, gives a roughly hour-long talk on Symbolics Lisp machines. It covers the machines and their environment from an insider's perspective.

Roman Elizarov compares Kotlin Coroutines with OpenJDK Project Loom virtual threads, looking at their design goals and how those translate into different implementations and tradeoffs. He addresses how the two can coexist.

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.

Christopher Domas's Derbycon 2015 talk on the M/o/Vfuscator, a compiler that emits only x86 mov instructions, showing mov is Turing complete. It explains how a full machine is built from mov and why the output is a nightmare to reverse engineer.

Cliff Click of Azul Systems gives a Google Tech Talk on running Java business applications on a machine with about a thousand cores. He covers hardware and software codesign, including garbage collection hardware and the JIT.

Matt Godbolt tells the story of Compiler Explorer, from a hacky basement server to a cloud-scaled service handling tens of thousands of daily requests. He also shows its features and how it is built.

A JuliaCon 2016 talk by Shashi Gowda showing an APL implementation in Julia. APL code is translated to Julia and JIT compiled to machine code.

James Mickens's humorous USENIX Security keynote argues that improving security and trusting opaque technology like machine learning is far harder than the industry admits.

Chuck Moore, inventor of Forth, presents GreenArrays' 144-core asynchronous chip at Strange Loop 2013. He explains how idle cores draw almost no power and how tight code minimizes energy use.

A short SIGBOVIK 2017 presentation by Tom Wildenhain showing that PowerPoint animations are Turing complete, with a working Turing machine built in slides. The talk is delivered deadpan as a serious research result.

Bryan Cantrill's Papers We Love talk on FreeBSD Jails and Solaris Zones, tracing how OS-level virtualization grew out of chroot and the limits of the traditional UNIX security model.

Valve's John McDonald presents at GDC 2018 on how Valve uses deep learning (VACnet) to detect cheaters in Counter-Strike: Global Offensive. He covers training on human-reviewed replays and how model output is confirmed by manual review.

A GDC 2018 talk by Valve's John McDonald on VACNet, a deep learning system that analyzes CS:GO gameplay to detect cheaters. It covers how the model is trained on human-reviewed Overwatch cases and how its output feeds human moderation.

Ron Pressler's Curry On 2015 talk arguing that imperative languages should not be polluted with pure functional concepts like monads. He favors simple blocking code over non-blocking styles.

David Beazley's PyData Global 2021 keynote, an oral history of early scientific Python. He tells how Python ended up running on a Connection Machine supercomputer at Los Alamos.

Ali Rahimi's NIPS 2017 Test-of-Time award talk, in which he argues that modern machine learning has become alchemy, working without being rigorously understood. He calls for more rigor and understanding in the field.

Eric Brandwine's AWS re:Invent 2015 session on how Amazon VPC networking works. It covers the problems the design solved, why traditional approaches do not scale, and the mechanisms used for customer isolation and VPC endpoints.

Joscha Bach's 35C3 talk offers an AI perspective on the soul, covering perception, mental representation, agency, consciousness and selfhood as things that can arise in a computational system like the brain.

Jose Valim introduces Nx, the project bringing numerical computing to Elixir, covering multi-dimensional tensors, automatic differentiation and JIT compilation to CPU and GPU.

David Ditzel of Esperanto Technologies presents their massively parallel, energy-efficient RISC-V processors at the 7th RISC-V Workshop in 2017. It covers the high-performance many-core design aimed at machine learning.