Modern High-Level Synthesis for Complex Data Science Applications

ISC 2023 Tutorial - Hall Y1 - 2nd Floor
Sunday, May 21, 2023 | 2:00 PM to 6:00 PM (CEST)

Giovanni Gozzi (Politecnico di Milano), Nicolas Bohm Agostini (Northeastern University and PNNL),

Fabrizio Ferrandi (Politecnico di Milano), Antonino Tumeo (PNNL)

Abstract

Field Programmable Gate Arrays (FPGAs) have become one of the key accelerators for data analytics and machine learning in the data center, and they are seeing increased adoption in heterogeneous high-performance computing systems for com-plex workflows that couple scientific simulation with data science. FPGAs have traditionally been programmed with hard-ware description languages, requiring significant engineering efforts and long development times. Today, the availability of new high-level synthesis (HLS) tools to generate accelerators starting from high-level specifications provides easier access to FPGAs and preserves programmer productivity. However, the conventional HLS flow typically starts from languages such as C, C++, or OpenCL, heavily annotated to provide information for the hardware generation, still leaving a significant gap with respect to the (Python based) data science frameworks. This tutorial will discuss HLS to accelerate data science on FPGAs, highlighting key methodologies, trends, advantages, benefits, but also gaps that still need to be closed.

The tutorial will provide a hands-on experience of the SOftware Defined Accelerators (SODA) Synthesizer, a toolchain composed of SODA-OPT, an opensource front-end and optimizer that interface with productive programming data science frameworks in Python, and Bambu, the most advanced open-source HLS tool available, able to generate optimized accelerators for data-intensive kernels.

Schedule

The time zone for all times mentioned at the ISC is CEST (GMT+2).

 

 

 

Reading list

✔    Papers:

o   Zhang, J.J., Agostini, N.B., Song, S., Tan, C., Limaye, A., Amatya, V., Manzano, J., Minutoli, M., Castellana, V.G., Tumeo, A. and Wei, G.Y., 2021, July. Towards Automatic and Agile AI/ML Accelerator Design with End-to-End Synthesis. In 2021 IEEE 32nd International Conference on Application-specific Systems, Architectures and Processors (ASAP) (pp. 218-225).

o   Ferrandi, F., Castellana, V.G., Curzel, S., Fezzardi, P., Fiorito, M., Lattuada, M., Minutoli, M., Pilato, C. and Tumeo, A., 2021, December. Bambu: an Open-Source Research Framework for the High-Level Synthesis of Complex Applications. In 2021 58th ACM/IEEE Design Automation Conference (DAC) (pp. 1327-1330).

o   Minutoli, M., Castellana, V.G., Saporetti, N., Devecchi, S., Lattuada, M., Fezzardi, P., Tumeo, A. and Ferrandi, F., 2021. Svelto: High-level synthesis of multi-threaded accelerators for graph analytics. IEEE Transactions on Computers.

o   Agostini, N.B., Curzel, S., Kaeli, D., and Tumeo, A., 2022, May, SODA-OPT an MLIR based flow for co-design and high-level synthesis. In 2022 Proceedings of the 19th ACM International Conference on Computing Frontiers (CF) (pp. 201–202).

o   Agostini, N.B., Curzel, S., Amatya, V., Tan, C., Minutoli, M., Castellana, V.G., Manzano, J., Kaeli, D., and Tumeo, A. 2022. An MLIR-based Compiler Flow for System-Level Design and Hardware Acceleration. In Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design (ICCAD '22), Article 6, (pp. 1-9)

o   Agostini, N.B., Curzel, S., Zhang, J.J., Limaye, A., Tan, C., Amatya, V., Minutoli, M., Castellana, V.G., Manzano, J., Brooks, D. and Wei, G.Y., 2022, June. Bridging Python to Silicon: The SODA Toolchain. In IEEE Micro, 42(5), (pp. 78–88).

✔    Additional material:

o   Other Bambu publications are listed on https://panda.dei.polimi.it/?page_id=177

o   Code repositories: https://github.com/ferrandi/PandA-bambu and https://gitlab.pnnl.gov/sodalite/soda-opt

Tutorial setup

✔    Have a computer with access to internet:

o   We will use a Jupiter Notebooks hosted on Google COLAB

▪       Notebook and material for Bambu: https://github.com/ferrandi/PandA-bambu/tree/feature/tutorial_isc23/documentation/tutorial_isc_2023

o   We will use Docker and a Jupiter Notebook:

▪       Notebook and material for SODA-OPT: https://gitlab.pnnl.gov/sodalite/soda-opt/-/blob/main/docs/tutorials/isc2023