For many years, we just compiled our languages either for x86 chips, or for a few platforms like the JVM that then compiled for that. But recently this has all started changing. First we have new compute platforms, such as GPUs and FPGAs. GPUs in particular are a really important compute platform now, and we want to be ableto target these with our programming languages. So far this has not been very easy, but this is starting to change. In addition, there are new software compilcation targets, such as Web Assembly, that is letting us program the web from any language. This track explores what is changing now and where we are going with languages and their compiler targets.
Track: Modern Compilation Targets
Location: Windsor, 5th flr.
Day of week: Tuesday
Track Host: Justin Cormack
Developer @Docker
Justin Cormack is a software engineer at Docker. He works on security, developer tooling and more. He is always interested in new programming language technology.
10:35am - 11:25am
Modern Compilation Targets
Session details to follow.
Anil Madhavapeddy, Docker Engineer, Leads OCaml Labs Group, & Lecturer @Cambridge_Uni
1:40pm - 2:30pm
TornadoVM: Java for GPUs and FPGAs
There is no single computer architecture that is best for executing all types of workloads efficiently. Therefore, the proliferation of heterogeneous hardware in recent years means that every system we program is likely to include a mix of computing elements; each of these with different hardware characteristics that enable programmers to improve performance while decreasing energy consumption. These new heterogeneous devices include multi-core CPUs, Graphics Processing Units (GPUs), and Field Programmable Gate Arrays (FPGAs). This trend has been followed by changes in software development norms that do not necessarily favor programmers.
A prime example is the two most popular heterogeneous programming languages, CUDA and OpenCL, which expose several low-level features to the API, making them difficult to use by non-expert users. Instead of using low-level programming languages, developers in industry and academia tend to use higher-level, object-oriented programming languages, typically executed on managed runtime environments, such as Java, R, Python, and JavaScript. Although many programmers might expect that such programming languages would have already been adapted for transparent execution on heterogeneous hardware, the reality is that their support is either very limited or absent.
In this talk, we present TornadoVM, a plugin for OpenJDK that allows Java programmers to automatically run on Heterogeneous Hardware such as multi-core CPUs, GPUs, and FPGAs. Furthermore, TornadoVM can perform live task-migration from one device to another entirely transparent for the user. To do so, TornadoVM consists of three software components: 1) A simple API for composing pipelines of existing Java methods. 2) An optimizing JIT compiler that extends the Graal compiler with hardware-aware optimizations that generate OpenCL C code. 3) A runtime system that executes TornadoVM specific bytecodes, it performs memory management. It also schedules the code for execution on GPUs, multi-core CPUs, and FPGAs, and it performs live task-migration between devices.
Juan Fumero, Research Associate @OfficialUoM (The University of Manchester)
2:55pm - 3:45pm
Build Your Own WebAssembly Compiler
For more than 20 years JavaScript has been the only 'native' language of the web. That's all changed with the release of WebAssembly. In the coming years, you'll see people writing web apps in Rust, C#, C++ and all manner of other languages. But just what is WebAssembly? And what’s all the fuss about?
WebAssembly is a low-level compilation target, which means that it is unlikely you’ll use it directly. However, as developers and hackers, we love to know how technology works!
In this talk, Colin will look at some of the internals of WebAssembly, explore how it works ‘under the hood’, and look at how you can create your own (simple) compiler that targets this runtime.
Colin Eberhardt, Technology Director @Scott_Logic
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