HPVM: Hardware-Agnostic Programming for Heterogeneous Parallel Systems

Adel Ejjeh, Aaron Councilman, Akash Kothari, Maria Kotsifakou, Leon Medvinsky, Abdul Rafae Noor, Hashim Sharif, Yifan Zhao, Sarita Adve, Sasa Misailovic, Vikram Adve

Research output: Contribution to journalArticlepeer-review


We present Heterogeneous Parallel Virtual Machine (HPVM), a compiler framework for hardware-agnostic programming on heterogeneous compute platforms. HPVM introduces a hardware-agnostic parallel intermediate representation with constructs for the hierarchical task, data, and pipeline parallelism, including dataflow parallelism, and supports multiple front-end languages. In addition, HPVM provides optimization passes that navigate performance, energy, and accuracy tradeoffs, and includes retargetable back ends for a wide range of diverse hardware targets, including central processing units, graphics processing units, domain-specific accelerators, and field-programmable gate arrays. Across diverse hardware platforms, HPVM optimizations provide significant performance and energy improvements, while preserving object-code portability. With these capabilities, HPVM facilitates developers, domain experts, and hardware vendors in programming modern heterogeneous systems.

Original languageEnglish (US)
Pages (from-to)108-117
Number of pages10
JournalIEEE Micro
Issue number5
StatePublished - 2022

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Electrical and Electronic Engineering


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