Outputs (15)

Building a Reusable and Extensible Automatic Compiler Infrastructure for reconfigurable devices (2023)
Presentation / Conference Contribution
Zang, Z., Dolinsky, U., Ghiglio, P., Cherubin, S., Goli, M., & Yang, S. (2023, September). Building a Reusable and Extensible Automatic Compiler Infrastructure for reconfigurable devices. Presented at FPL 2023: 33rd International Conference on Field-Progr

Multi-Level Intermediate Representation (MLIR) is gaining increasing attention in reconfigurable hardware communities due to its capability to represent various abstract levels for software compilers. This project aims to be the first to provide an e... Read More about Building a Reusable and Extensible Automatic Compiler Infrastructure for reconfigurable devices.

Clever DAE: Compiler Optimizations for Digital Twins at Scale (2023)
Presentation / Conference Contribution
Scuttari, M., Camillucci, N., Cattaneo, D., Agosta, G., Casella, F., Cherubin, S., & Terraneo, F. (2023). Clever DAE: Compiler Optimizations for Digital Twins at Scale. In CF '23: Proceedings of the 20th ACM International Conference on Computing Frontier

Modeling and simulation are fundamental activities in engineering to facilitate prototyping, verification and maintenance. Declarative modeling languages allow to simulate physical phenomena by expressing them in terms of Differential and Algebraic E... Read More about Clever DAE: Compiler Optimizations for Digital Twins at Scale.

TAFFO: The compiler-based precision tuner (2022)
Journal Article
Cattaneo, D., Chiari, M., Agosta, G., & Cherubin, S. (2022). TAFFO: The compiler-based precision tuner. SoftwareX, 20, Article 101238. https://doi.org/10.1016/j.softx.2022.101238

We present taffo, a framework that automatically performs precision tuning to exploit the performance/accuracy trade-off. In order to avoid expensive dynamic analyses, taffo leverages programmer annotations which encapsulate domain knowledge about th... Read More about TAFFO: The compiler-based precision tuner.

Ahead-Of-Real-Time (ART): A Methodology for Static Reduction of Worst-Case Execution Time (2022)
Presentation / Conference Contribution
Cattaneo, D., Magnani, G., Cherubin, S., & Agosta, G. (2022). Ahead-Of-Real-Time (ART): A Methodology for Static Reduction of Worst-Case Execution Time. In Third Workshop on Next Generation Real-Time Embedded Systems (NG-RES 2022) (4:1-4:10). https://doi

Precision tuning is an approximate computing technique for trading precision with lower execution time, and it has been increasingly important in embedded and high-performance computing applications. In particular, embedded applications benefit from... Read More about Ahead-Of-Real-Time (ART): A Methodology for Static Reduction of Worst-Case Execution Time.

13th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 11th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM 2022) (2022)
Presentation / Conference Contribution
Palumbo, F., Bispo, J., & Cherubin, S. (2022). 13th Workshop on Parallel Programming and Run-Time Management Techniques for Many-Core Architectures and 11th Workshop on Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM

Architecture-aware Precision Tuning with Multiple Number Representation Systems (2021)
Presentation / Conference Contribution
Cattaneo, D., Chiari, M., Fossati, N., Cherubin, S., & Agosta, G. (2021). Architecture-aware Precision Tuning with Multiple Number Representation Systems. In 2021 58th ACM/IEEE Design Automation Conference (DAC). https://doi.org/10.1109/dac18074.2021.958

Precision tuning trades accuracy for speed and energy savings, usually by reducing the data width, or by switching from floating point to fixed point representations. However, comparing the precision across different representations is a difficult ta... Read More about Architecture-aware Precision Tuning with Multiple Number Representation Systems.

FixM: Code generation of fixed point mathematical functions (2020)
Journal Article
Cattaneo, D., Chiari, M., Magnani, G., Fossati, N., Cherubin, S., & Agosta, G. (2021). FixM: Code generation of fixed point mathematical functions. Sustainable Computing, 29, part B, Article 100478. https://doi.org/10.1016/j.suscom.2020.100478

Approximate computing has seen significant interest as a design philosophy oriented to performance and energy efficiency [1]. Precision tuning is an approximate computing technique that trades off the accuracy of operations for performance and energy... Read More about FixM: Code generation of fixed point mathematical functions.

Dynamic Precision Autotuning with TAFFO (2020)
Journal Article
Cherubin, S., Cattaneo, D., Chiari, M., & Agosta, G. (2020). Dynamic Precision Autotuning with TAFFO. ACM transactions on architecture and code optimization, 17(2), Article 10. https://doi.org/10.1145/3388785

Many classes of applications, both in the embedded and high performance domains, can trade off the accuracy of the computed results for computation performance. One way to achieve such a trade-off is precision tuning—that is, to modify the data types... Read More about Dynamic Precision Autotuning with TAFFO.

Tunable approximations to control time-to-solution in an HPC molecular docking Mini-App (2020)
Journal Article
Gadioli, D., Palermo, G., Cherubin, S., Vitali, E., Agosta, G., Manelfi, C., …Silvano, C. (2021). Tunable approximations to control time-to-solution in an HPC molecular docking Mini-App. Journal of Supercomputing, 77(1), 841-869. https://doi.org/10.1007

The drug discovery process involves several tasks to be performed in vivo, in vitro and in silico. Molecular docking is a task typically performed in silico. It aims at finding the three-dimensional pose of a given molecule when it interacts with the... Read More about Tunable approximations to control time-to-solution in an HPC molecular docking Mini-App.

Tools for Reduced Precision Computation: A Survey (2020)
Journal Article
Cherubin, S., & Agosta, G. (2020). Tools for Reduced Precision Computation: A Survey. ACM computing surveys, 53(2), Article 33. https://doi.org/10.1145/3381039

The use of reduced precision to improve performance metrics such as computation latency and power consumption is a common practice in the embedded systems field. This practice is emerging as a new trend in High Performance Computing (HPC), especially... Read More about Tools for Reduced Precision Computation: A Survey.