![The Challenge ,[object Object],[object Object],[object Object],[object Object],Data from Kunle Olukotun, Lance Hammond, Herb Sutter, Burton Smith, Chris Batten, and Krste Asanovic](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
Recommandé
Contenu connexe
Tendances
Tendances (20)
Similaire à Oscon keynote: Working hard to keep it simple
Similaire à Oscon keynote: Working hard to keep it simple (20)
Plus de Martin Odersky
Plus de Martin Odersky (17)
Dernier
Dernier (20)
Oscon keynote: Working hard to keep it simple
- 1. Working Hard to Keep it Simple Martin Odersky Typesafe
- 5. Space vs Time Time (imperative/concurrent) Space (functional/parallel)
- 6. Scala is a Unifier Agile, with lightweight syntax Object-Oriented Scala Functional Safe and performant, with strong static tpying
- 7. Scala is a Unifier Agile, with lightweight syntax Parallel Object-Oriented Scala Functional Sequential Safe and performant, with strong static tpying
- 10. Scala’s Toolbox
- 18. EPFL / Stanford Research Applications Domain Specific Languages Heterogeneous Hardware DSL Infrastructure OOO Cores SIMD Cores Threaded Cores Specialized Cores Programmable Hierarchies Scalable Coherence Isolation & Atomicity On-chip Networks Pervasive Monitoring Domain Embedding Language ( Scala ) Virtual Worlds Personal Robotics Data informatics Scientific Engineering Physics ( Liszt ) Scripting Probabilistic (RandomT) Machine Learning ( OptiML ) Rendering Parallel Runtime ( Delite, Sequoia, GRAMPS ) Dynamic Domain Spec. Opt. Locality Aware Scheduling Staging Polymorphic Embedding Task & Data Parallelism Hardware Architecture Static Domain Specific Opt.
Notes de l'éditeur
- This leads to our vision, applications driven by a set of interoperable DSLs. We are developing DSLs to provide evidence as to their effectiveness in extracting parallel performance. But we are also very interested in empowering other to easily build such DSLs, so we are investing heavily in developing frameworks and runtimes to make parallel DSL development easier. And the goal is to run single source programs on a variety of very different hardware targets.
- Liszt is another language we have implemented. It is designed to support the creation of solvers for mesh-based partial differential equations. Problems in this domain typically simulate complex physical systems such as fluid flow or mechanics by breaking up space into discrete cells. A typical mesh may contain hundreds of millions of these cells (here we are visualizing a scram-jet designed to work at hypersonic speeds). Liszt is an ideal candidate for a DSL because while the problems are large and highly parallel, the mesh introduces many data-dependencies that are difficult to reason about, making writing solvers tedious.