Category Archives: Conferences

[QCon 2019] Maximizing Performance with GraalVM

Posted on by
Reply

Thomas Wuerthinger 

For other QCon blog posts, see QCon live blog table of contents

Tradeoff between what factors optimized

  • Startup time
  • Peak throughput
  • Memory footprint
  • Maximizing request latency
  • Packaging size (matters for mobile)
  • Can usually optimize a few (but not all) of these

GraalVM

  • Supports JVM languages, Rubby, Python, C, Rust, R etc
  • Can embed in node js, oracle database
  • Standalone binary
  • Community Edition and Enterprise Edition
  • Can run with Open JDK using Graal JIT compiler or AOT (ahead of time compiling)

AOT

  • To use, create new binary with pre-compiled code
  • Package classes from app, libraries used and part of the VM
  • Iterate adding things until know what need. Then create native executable.
  • Uses an order of magnitude less memory than JIT. Saving memory helps when running on AWS Lambda
  • CPU usage a lot less up front. Small peak at startup
  • JIT compiler has profiling feedback so can do better in the long run. AOT has PGO (profile guided optimizations) to deal with this
  • Working on improving – collecting profiles up front, low latency GC option and tracing agent to facilitate configuration

Performance

  • Startup time (from start until first request can be served). Two orders of magnitude faster with AOT
  • Starting up in less than 50 milliseconds allows spinning up new process upon request
  • Hard to measure. Can be lucky/unlucky when get data.
  • JIT has an advantage for peak performance. It has profiling data and can make optimistic assumptions. If the assumption not true, can de-optimize/bail out of optimization.

Benchmarks

  • Benchmarks are good. Should have more
  • Optimizing on too few benchmarks is like overfitting on machine learning
  • http://renaissance.dev/ – benchmark suite. Includes Scala and less commonly tested

Choosing

  • GraalVM JIT – when need peak throughput, max latency and no config
  • GraalVM AOT – use when need fast startup time, small memory footprint and small packaging size

Recommends reading top 10 things to do with GraalVM

Q&A

  • Have you considered using Epsilon in benchmark? Not yet. Makes sense since doesn’t do any GC
  • Why not use parallel GC? Not sure if it would make a difference. Kirk noted would avoid allocation hit over G1.
  • Does AOT make sense for large heaps? Can make sure don’t have disadvantage at least.

My impressions

I had heard about Graal and forgotten a lot. I re-learned much. I like the list of steps slides and the diagram. I feel like it will be more memorable this time. I also liked the comparison at the end on impact of the dimensions covered up front.

[QCon 2019] Java Futures

Posted on by
Reply

Brian Goetz

For other QCon blog posts, see QCon live blog table of contents

General

  • Java is approaching middle age. Almost 25 years old
  • Keep promises to users
  • Prime directive is compatibility
  • Backward compatibility matters ex: generics. Don’t need to recompile old code
  • Patterns ex: single method interfaces for lambdas rather than having to rewrite libraries
  • Languages features are forever. Interacts with others; even future ones
  • Waited 10 years for generics until had right story/timing. Knew copying C++ was the wrong choice
  • No language is ever finished
  • Languages are never good enough because hardware changes, new problems, developer expectations change
  • mid-2019 edition because things change so fast

Cadence

  • Used to release based on a feature rather than a data
  • Often didn’t feel worthwhile to do small feature because got stuck behind big ones
  • Now doing about two years of six month release schedule.
  • Release management overhead went down to almost zero
  • Same rate of innovation; just changed rate of release
  • Java 13 already in rampdown. Released in September.
  • Already working on Java 14

Preview feature

  • Risk of things happening too quickly since features are forever
  • Preview means feature is done but not finalized
  • Not experimental/beta.
  • Think of as provisional feature.
  • Expected outcome is that will be promoted to real feature in next version or two
  • Full IDE/Tooling support for preview features
  • Need to turn them on so not accidentally using in production -enable-preview flag

Current initiatives

  • Amber – right sizing language ceremony. Includes local variable type inference and future changes like pattern matching
  • Valhalla – adapt form modern hardware, value types, generic specialization
  • Loom – Fibers
  • Panama – Native code and data

Local Variable type inference

  • In Java 10. Future if on Java 8. Infinite past if you are Brian :).
  • var instead of type for local variable
  • Not syntactic sugar. Can expose “hidden” type (ex: capture types, intersection types and anonymous class types). So see more generics.
  • One of most commonly requested features
  • But also significant/vocal angst – can write bad code; giving into fashion
  • Not controversial once release. Fear of change in advance?
  • Will take time for good practices to emerge
  • Style guide https://openjdk.java.net/projects/amber/LVTIstyle.html

Switch enhancements

  • Preview feature in Java 12 and 13
  • Significant fraction of switch statements want to be expression. SO have to assign in each case.
  • Break is annoying. Irritating and error prone
  • Looked at how switch statements needs to evolve for pattern matching and then made more generally useful.
  • Boilerplate bad because a place for bugs to hide
  • Two changes – can use switch as expression or statement. Streamlined syntax label -> consequence
  • Will be in Java 14 unless feedback said made some horrible error

Multi-line String literals

  • Preview feature in Java 13
  • Require quotes and concatenation. Error prone for JSON, SQL and HTML
  • Manual mangling introduces errors
  • Was going to be a preview feature in Java 12. WIthdrawn because had better idea of how to do it.
  • Triple quotes to start/end
  • Dots for indentation that is just for IDE so don’t get extra whitespace when reformat in IDE.

Pattern matching

  • Intend to deliver in phases; hopefully starting in Java 14
  • Phase 1
    • Replaces if statement for instanceof and then the cast for the same
    • “Not only does the language make you cast explicitly, but it gives you the change to get it wrong”
    • if (a instanceof Integer intvalue) – checks type and gives new variable can use as type safely
    • Simplifies equals method implementation
  • Phase 2
    • Use in switch
    • case Integer i – matches if Integer, bind to i and allow use of variable inside the case.

Records

  • Lots of boilerplate – constructor, accessors, Object methods
  • A lot of code to read only to find out didn’t need to read any of it.
  • IDE generates boilerplate, but it doesn’t help you read it.
  • record Point(int x, int y) {}
  • Like enum, give up some extra features to get functionality.
  • Get sensible defaults in record
  • Declaratively states “I am simply a carrier for my data”
  • Programmer making a commitment
  • [does this discourage adding instance methods?]
  • Product type of algebraic data type

Sealed types

  • Sum type of algebraic data types
  • Shape = Circle + Rect
  • Compiler will know only those types
  • sealed interface Shape {}
  • record Circle(Point center, int radius) implements Shape {}
  • record Rect(Point x,….
  • Can use in if statement and pattern matching to get fields of record as local variables
  • Can use in switch statement. Compiler will complain if don’t address all possible implementations of sealed types
  • ex: case Circle(Var center, var r) -> PI * r * r;

Project Valhalla

  • Aims to reboot the layout of data in memory
  • Hardware change a lot in past 25 years.
  • Cost of memory fetch vs arithmetic has increased heavily in last 25 years
  • An array of objects will use data all over so many cache misses
  • Big change because goes down so far.
  • We want to be able to specify the class should be inlined
  • Giving up immutability and representation polymorphism.
  • Getting hardware friendly data layout
  • Code for the class works like an int

My Impressions

Great talk! It covered both things I had seen and things I hadn’t. Great perspective. Excited for some of the coming features.

[QCon 2019] No Moore Left to Give

Posted on by
Reply

Bryan Cantrill

For other QCon blog posts, see QCon live blog table of contents

Moore’s law

  • Not about speed, # transistors, density or per dollar
  • Not coined by Moore
  • Came from paper in 1965 – “Cramming more components onto integrated circuits:
  • Term coined in 1971 when Carver Mead was talking to a journalist
  • Moore also predicated home computers and computers onboard cars. Predicting 40 years out accurately is hard.
  • Predicted lower costs
  • In 1975, Moore updated the law to be a doubling of transistor density every two years. Meant to be a way of motivating engineers.
  • An Intel executive said 18 months (vs 2 years) and that got quoted all over.

Implications

  • Apps don’t get twice as fast.
  • Hit memory wall
  • Moore’s Law could add more caching, but that can only get so far
  • Need Symmetric Multi Processing to increase throughput
  • Speculative execution tried to pre-execute code and then became a security issue
  • Cost matters. It’s not about increasing speed at any cost

End of Moore’s Law

  • Samsung trying to 3 nanometer.
  • Many unsolved problems
  • A silicon atom is .2 nanometers.
  • This is the end. Can’t physically make smaller. 3 nanometers is only 15 atoms across
  • 7 nanometers might be the smallest size at a reasonable cost.

Beyond Moore’s Law – Quantum

  • Quantum computer is surprisingly really
  • Need large refrigerator. Must be close to absolute zero
  • Problem domain is very limited
  • Scale is tiny
  • Don’t yet have ability to scale qbits
  • Quantum computing may be relevant one day for the enterprise, but not any time soon

Beyond Moore’s Law – Specialized Compute

  • Bitcoin mining
  • GPGPU for ML/DL (machine learning/deep learning)

Beyond Moore’s Law – 3D

  • Heat and cost problems
  • Intel working on (Foveros)
  • Not a way to get “back on track” for Moore’s law

Beyond Moore’s Law – 2.5D

  • Smaller chiplets that are integrated on a larger die through silicon
  • Can be different types and sizes
  • Intel investing in this as well.

Beyond Moore’s Law – Alternate Tech

  • Carbon nanotubes, phase change memory, etc
  • History indicates won’t be able to compete on economics
  • If/when break through, change industry
  • Flash memory is only example of a break through like this

Beyond Moore’s Law – Wright’s Law

  • Cost of manufacturing an aircraft dropped 10-15% which volume doubled
  • Learning curve effect
  • Possible chips will get cheaper again as product goes up.

My impressions

This was great! He has amazing energy. It was a topic that was interesting and general interest. (I missed some of this because I was excited and communicating about being a Java Champion!). The state of the art and future is cool to hear about!