Silvio Bacci
Research Subjects
Research Interests
Silvio Bacci has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Alessandro Druetto
Computer Science Department, University of Turin, Corso Svizzera 185, 10149 Torino, Italy
1 shared publication - Andrea Grosso
Università di Torino
1 shared publication - Enrico Bini
University of Turin
1 shared publication - Francesco Paladino
Scuola Superiore Sant'Anna, Pisa, Italy
1 shared publication - Marco Di Natale
Scuola Superiore Sant'Anna, Pisa, Italy
1 shared publication - Stefano Puri
Huawei Pisa Research Center, Italy
1 shared publication
Latest Publications
- Open Access
- 7 June 2023
- Published by Association for Computing Machinery (ACM)
- p. 166-176
Task and Memory Mapping of Large Size Embedded Applications over NUMA architecture✱
Multicore architectures provide the increased performance required by modern embedded real-time systems. Most platforms exhibit a non-uniform memory access (NUMA). In NUMA, memory banks with different access time can be explicitly addressed. Such an architecture, however, is challenging predictability given the significant impact of the allocation of variables on the execution times. At software level, real-world embedded applications (e.g. automotive) are composed by thousands of functions often communicating through shared variables stored in memory, with a variable access time because of NUMA. This paper addresses the mapping of complex embedded applications onto NUMA multicore architectures. The developed problem formulation offers a solution to the following problems: (i) allocating variables (called labels in the automotive context) over memories of different characteristics, (ii) mapping functionalities (called runnables) onto CPUs, (iii) creating OS tasks from runnables, and (iv) assigning priorities to tasks. Our developed implementation is capable to handle an application composed by 1K+ runnables, all sharing 10K+ labels and finds a solution in at most 3 minutes on a standard laptop, enabling interactive design space exploration.
- 7 June 2023
- Published by Association for Computing Machinery (ACM)
- p. 166-176
Open AccessTask and Memory Mapping of Large Size Embedded Applications over NUMA architecture✱
Multicore architectures provide the increased performance required by modern embedded real-time systems. Most platforms exhibit a non-uniform memory access (NUMA). In NUMA, memory banks with different access time can be explicitly addressed. Such an architecture, however, is challenging predictability given the significant impact of the allocation of variables on the execution times. At software level, real-world embedded applications (e.g. automotive) are composed by thousands of functions often communicating through shared variables stored in memory, with a variable access time because of NUMA. This paper addresses the mapping of complex embedded applications onto NUMA multicore architectures. The developed problem formulation offers a solution to the following problems: (i) allocating variables (called labels in the automotive context) over memories of different characteristics, (ii) mapping functionalities (called runnables) onto CPUs, (iii) creating OS tasks from runnables, and (iv) assigning priorities to tasks. Our developed implementation is capable to handle an application composed by 1K+ runnables, all sharing 10K+ labels and finds a solution in at most 3 minutes on a standard laptop, enabling interactive design space exploration.