A well-defined system-level model contains explicit parallelism and should be free from parallel access conflicts to shared variables. However, safe parallelism is difficult to achieve since risky shared variables are often hidden deep in the design and are not exposed through simulation. In this paper, we propose a new static analysis approach based on segment graphs that identifies a tight set of potential access conflicts in segments that may-happen-in-parallel (MHP). Our experimental results show that the analysis is complete, accurate and fast to reveal dangerous shared variables in several embedded application models. Compared to earlier work, our approach significantly reduces the number of false conflict reports and thus saves the designer time.

The validation of system models at the transaction-level typically relies on discrete event (DE) simulation. In order to reduce simulation time, parallel discrete event simulation (PDES) can be used by utilizing multiple cores available on today's host PCs. However, the total order of time imposed by regular DE simulators becomes a bottleneck that severely limits the benefits of parallel simulation. In this paper, we present a new out-of-order (OoO) PDES technique for simulating transaction-level models on multicore hosts. By localizing the simulation time to individual threads and carefully handling events at different times, a system model can be simulated following a partial order of time without loss of accuracy. Subject to advanced static analysis at compile time and table-based decisions at run time, threads can be issued early, reducing the idle time of available cores. Our proposed OoO PDES technique shows high performance gains in simulation speed with only a small increase in compile time. Using six embedded application examples, we also show the speed trade-off for multicore PDES based on different multithreading libraries.

Describing Multi-Processor Systems-on-Chip (MPSoC) at the abstract Electronic System Level (ESL) is one task, validating them efficiently is another. Here, fast and accurate system-level simulation is critical. Recently, Parallel Discrete Event Simulation (PDES) has gained significant attraction again as it promises to utilize the existing parallelism in today's multicore CPU hosts. This paper discusses the parallel simulation of Transaction-Level Models (TLMs) described in System-Level Description Languages (SLDLs), such as SystemC and SpecC.We review how PDES exploits the explicit parallelism in the ESL design models and uses the parallel processing units available on multicore host PCs to significantly reduce the simulation time. We show experimental results for two highly parallel benchmarks as well as for two actual embedded applications.

At the Electronic System Level (ESL), design validation often relies on discrete event (DE) simulation. Recently, parallel simulators have been proposed which increase simulation speed by using multiple cores available on today's PCs. However, the total order of time in DE simulation is a bottleneck that severely limits the benefits of parallel simulation. This paper presents a new out-of-order simulator for multi-core parallel DE simulation of hardware/software designs at any abstraction level. By localizing the simulation time and carefully handling events at different times, a system model can be simulated following a partial order of time. Subject to automatic static data analysis at compile time and table-based decisions at run time, threads can be issued early which reduces the idle time of available cores. Our experiments show high performance gains in simulation speed with only a small increase of compile time.

The validation of transaction level models described in System-level Description Languages (SLDLs) often relies on extensive simulation. However, traditional Discrete Event (DE) simulation of SLDLs is cooperative and cannot utilize the available parallelism in modern multi-core CPU hosts. In this work, we study the SLDL execution semantics of concurrent threads and present a multi-core parallel simulation approach which automatically protects communication between concurrent threads so that parallel simulation on multi-core hosts becomes possible. We demonstrate significant speed-up in simulation time of several system models, including a H.264 video decoder and a JPEG encoder.