Kernels for the DPHPC project can be run on the following branches:
This repository hosts the hardware and software for the Snitch cluster and its generator. Snitch is a high-efficiency compute cluster platform focused on floating-point workloads. It is developed as part of the PULP project, a joint effort between ETH Zurich and the University of Bologna.
To get started, check out the getting started guide.
What can you expect to find in this repository?
- The RISC-V Snitch integer core. This can be useful stand-alone if you are just interested in re-using the core for your project, e.g., as a tiny control core or you want to make a peripheral smart. The sky is the limit.
- The Snitch cluster. A highly configurable cluster containing one to many integer cores with optional floating-point capabilities as well as our custom ISA extensions
Xssr
,Xfrep
, andXdma
. - A runtime and example applications for the Snitch cluster.
- RTL simulation environments for Verilator, Questa Advanced Simulator, and VCS, as well as configurations for our Banshee system simulator
This code was previously hosted in the Snitch monorepo and was spun off into its own repository to simplify maintenance and dependency handling. Note that our Snitch-based manycore system Occamy has also moved.
verilator >= v4.1
bender >= v0.27.0
Snitch is being made available under permissive open source licenses.
The following files are released under Apache License 2.0 (Apache-2.0
) see LICENSE
:
sw/
util/
The following files are released under Solderpad v0.51 (SHL-0.51
) see hw/LICENSE
:
hw/
The sw/deps
directory references submodules that come with their own
licenses. See the respective folder for the licenses used.
sw/deps/
If you use the Snitch cluster or its extensions in your work, you can cite us:
Snitch: A tiny Pseudo Dual-Issue Processor for Area and Energy Efficient Execution of Floating-Point Intensive Workloads
@article{zaruba2020snitch,
title={Snitch: A tiny Pseudo Dual-Issue Processor for Area and Energy Efficient Execution of Floating-Point Intensive Workloads},
author={Zaruba, Florian and Schuiki, Fabian and Hoefler, Torsten and Benini, Luca},
journal={IEEE Transactions on Computers},
year={2020},
publisher={IEEE}
}
Stream semantic registers: A lightweight risc-v isa extension achieving full compute utilization in single-issue cores
@article{schuiki2020stream,
title={Stream semantic registers: A lightweight risc-v isa extension achieving full compute utilization in single-issue cores},
author={Schuiki, Fabian and Zaruba, Florian and Hoefler, Torsten and Benini, Luca},
journal={IEEE Transactions on Computers},
volume={70},
number={2},
pages={212--227},
year={2020},
publisher={IEEE}
}
Indirection Stream Semantic Register Architecture for Efficient Sparse-Dense Linear Algebra
@inproceedings{scheffler2021indirect,
author={Scheffler, Paul and Zaruba, Florian and Schuiki, Fabian and Hoefler, Torsten and Benini, Luca},
booktitle={2021 Design, Automation & Test in Europe Conference & Exhibition (DATE)},
title={Indirection Stream Semantic Register Architecture for Efficient Sparse-Dense Linear Algebra},
year={2021},
volume={},
number={},
pages={1787-1792}
}
MiniFloat-NN and ExSdotp: An ISA Extension and a Modular Open Hardware Unit for Low-Precision Training on RISC-V Cores
@inproceedings{bertaccini2022minifloat,
author={Bertaccini, Luca and Paulin, Gianna and Fischer, Tim and Mach, Stefan and Benini, Luca},
booktitle={2022 IEEE 29th Symposium on Computer Arithmetic (ARITH)},
title={MiniFloat-NN and ExSdotp: An ISA Extension and a Modular Open Hardware Unit for Low-Precision Training on RISC-V Cores},
year={2022},
volume={},
number={},
pages={1-8}
}
Soft Tiles: Capturing Physical Implementation Flexibility for Tightly-Coupled Parallel Processing Clusters
@inproceedings{paulin2022softtiles,
author={Paulin, Gianna and Cavalcante, Matheus and Scheffler, Paul and Bertaccini, Luca and Zhang, Yichao and Gürkaynak, Frank and Benini, Luca},
booktitle={2022 IEEE Computer Society Annual Symposium on VLSI (ISVLSI)},
title={Soft Tiles: Capturing Physical Implementation Flexibility for Tightly-Coupled Parallel Processing Clusters},
year={2022},
volume={},
number={},
pages={44-49},
doi={10.1109/ISVLSI54635.2022.00021}
}