Metadata only
Date
2020Type
- Conference Paper
Abstract
Spatial computing architectures pose an attractive alternative to mitigate control and data movement overheads typical of load-store architectures. In practice, these devices are rarely considered in the HPC community due to the steep learning curve, low productivity, and the lack of available libraries for fundamental operations. High-level synthesis (HLS) tools are facilitating hardware programming, but optimizing for these architectures requires factoring in new transformations and resources/performance trade-offs. We present FBLAS, an open-source HLS implementation of BLAS for FPGAs, that enables reusability, portability and easy integration with existing software and hardware codes. FBLAS' implementation allows scaling hardware modules to exploit on-chip resources, and module interfaces are designed to natively support streaming on-chip communications, allowing them to be composed to reduce off-chip communication. With FBLAS, we set a precedent for FPGA library design, and contribute to the toolbox of customizable hardware components necessary for HPC codes to start productively targeting reconfigurable platforms. © 2020 IEEE Show more
Publication status
publishedExternal links
Book title
SC20: Proceedings of the International Conference for High Performance Computing, Networking, Storage and AnalysisPages / Article No.
Publisher
IEEEEvent
Subject
Spatial architectures; high level synthesis; hardware libraryOrganisational unit
03950 - Hoefler, Torsten / Hoefler, Torsten
Funding
678880 - DAPP: Data-Centric Parallel Programming (EC)
801039 - Exascale Programming Models for Heterogeneous Systems (EC)
Related publications and datasets
Notes
Conference lecture held on November 18, 2020. Due to the Coronavirus (COVID-19) the conference was conducted virtually.More
Show all metadata