By Rainer Leupers, Olivier Temam
Processor and System-on-Chip Simulation Edited via: Rainer Leupers Olivier Temam the present pattern from monolithic processors to multicore and multiprocessor structures on chips (MPSoC) with tens of cores and gigascale integration makes structure and software program layout an increasing number of advanced and expensive. as a result, simulation know-how has develop into an incredibly vital pre-silicon verification and optimization car. Simulation of laptop architectures has made fast development lately. the first software components are hardware/software functionality estimation and optimization, in addition to sensible and timing verification. fresh, leading edge applied sciences, corresponding to retargetable simulator iteration, dynamic binary translation and sampling simulation have enabled common use of processor and system-on-chip (SoC) simulation instruments within the semiconductor and embedded process industries. This booklet provides and discusses the primary applied sciences and state of the art in high-level structure software program simulation, either on the processor and the system-on-chip point. • provides cutting-edge and destiny traits in processor and SoC simulation; • Demonstrates how simulation is helping to spice up and software program layout productiveness; • Addresses simulation standards and applied sciences within the multicore context; • Covers process features, comparable to digital systems, bus simulation, caches, energy, and layout house exploration.
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2). A Simics model exposes an arbitrary set of interfaces to other models in other modules, and objects can call any model interface in any module. Interfaces are used between device models to model hardware communication paths and to implement other simulator functionality and information flows, such as getting the current cycle count of a processor or finding the address of a variable from the debug module. Unlike SystemC, multiple objects may call the same interface and bindings are not made at compile time.
However, almost every new system contains some new and unique device models. Thus, device modeling tends to be the main effort when modeling a new target system. The devices, processors, memories, and interconnects are then combined into a hierarchical structure that is called components in Simics terminology. As illustrated in Fig. 5, Simics components describe processor clusters, SoCs, memories, boards, racks, and other aggregates in a system. They are implemented as Python code, affording users flexibility in describing recurring and dynamic structures.
Checkpointing, as it is known today, first appeared in full-system simulators in the mid-1990s . The primary use case at that time was to change the level of abstraction, from a fast functional model to a detailed model, using the fast model to position a workload at an interesting point. This technique is still in use today, supporting both computer architecture research and detailed software performance analysis [1, 6–8]. The key implementation mechanism for checkpointing in Simics is the attribute system.