TY - GEN
T1 - FBLAS: Streaming linear algebra on FPGA
AU - Matteis, Tiziano De
AU - Licht, Johannes De Fine
AU - Hoefler, Torsten
N1 - Published online: 22 February 2021
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85102392423
U2 - 10.1109/SC41405.2020.00063
DO - 10.1109/SC41405.2020.00063
M3 - Conference contribution
SN - 9781728199993
T3 - International Conference for High Performance Computing, Networking, Storage and Analysis, SC
BT - Proceedings of SC 2020
PB - IEEE Computer Society
T2 - 2020 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2020
Y2 - 9 November 2020 through 19 November 2020
ER -