Computer Science > Programming Languages
[Submitted on 3 Nov 2016]
Title:HPVM: A Portable Virtual Instruction Set for Heterogeneous Parallel Systems
View PDFAbstract:We describe a programming abstraction for heterogeneous parallel hardware, designed to capture a wide range of popular parallel hardware, including GPUs, vector instruction sets and multicore CPUs. Our abstraction, which we call HPVM, is a hierarchical dataflow graph with shared memory and vector instructions. We use HPVM to define both a virtual instruction set (ISA) and also a compiler intermediate representation (IR). The virtual ISA aims to achieve both functional portability and performance portability across heterogeneous systems, while the compiler IR aims to enable effective code generation and optimization for such systems.
HPVM effectively supports all forms of parallelism used to achieve computational speedups (as opposed to concurrency), including task parallelism, coarse-grain data parallelism, fine-grain data parallelism, and pipelined parallelism. HPVM also enables flexible scheduling and tiling: different nodes in the dataflow graph can be mapped flexibly to different combinations of compute units, and the graph hierarchy expresses memory tiling, essential for achieving high performance on GPU and CPU targets.
References & Citations
Bibliographic and Citation Tools
Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)
Code, Data and Media Associated with this Article
alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)
Demos
Recommenders and Search Tools
Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.