Proper tools and workloads are required to evaluate any computing systems. This enables designers to fulfill the desired properties expected by the end-users. It can be observed that multi/many-core chips are omnipresent from small-to-large-scale systems, such as mobile phones and data centers. The reliance on multi/many-core chips is increasing as they provide high-processing capability to meet the increasing performance requirements of complex applications in various application domains. The high-processing capability is achieved by employing parallel processing on the cores where the application needs to be partitioned into a number of tasks or threads and they need to be efficiently allocated onto different cores. The applications considered for evaluations represent workloads and toolchains required to facilitate the whole evaluation are referred to as tools. The tools facilitate realization of different actions (e.g., thread-to-core mapping and voltage/frequency control, which are governed by OS scheduler and power governor, respectively) and their effect on different performance monitoring counters leading to a change in the performance metrics (e.g., energy consumption and execution time) concerned by the end-users.

Chapter Contents:

• 5.1 Single-chip multi/many-core systems
• 5.1.1 Tools
• 5.1.2 Workloads
• 5.2 Multi-chip multi/many-core systems
• 5.2.1 Tools
• 5.2.2 Workloads
• 5.3 Discussion
• 5.4 Conclusion and future directions
• 5.4.1 Parallelization of real-world applications
• 5.4.2 Domain-specific unification of workloads
• 5.4.3 Unification of simulation tools
• 5.4.4 Integration of tools to real products
• References

Inspec keywords: parallel processing; processor scheduling; multiprocessing systems; power aware computing

Other keywords: parallel processing; manycore computing; toolchains; high-processing capability; small-to-large-scale systems; complex applications; performance monitoring counters; multicore chips; OS scheduler

Subjects: Multiprocessing systems; Parallel software; Performance evaluation and testing; Parallel programming and algorithm theory