Scaling up the system size has been the common approach to achieving high performance in parallel computing. However, designing and implementing a large-scale parallel system can be very costly in terms of money and time. When building a target system, it is desirable to initially build a smaller version by using the processing nodes with the same architecture as those in the target system. This allows us to achieve efficient and scalable prediction by using the smaller system to predict the performance of the target system. Such scalability prediction is critical because it enables system designers to evaluate different design alternatives so that a certain performance goal can be successfully achieved. As the de facto standard for writing parallel applications, MPI is widely used in large-scale parallel computing. By categorizing the discrete event simulation methods for MPI programs and analyzing the characteristics of scalability prediction, we propose a novel simulation method, called virtual-actual combined execution-driven (VACED) simulation, to achieve scalable prediction for MPI programs. The basic idea behind is to predict the execution time of an MPI program on a target machine by running it on a smaller system so that we can predict its communication time by virtual simulation and obtain its sequential computation time by actual execution. We introduce a model for the VACED simulation as well as the design and implementation of VACED-SIM, a lightweight simulator based on fine-grained activity and event definitions. We have validated our approach on a sub-system of Tianhe-1A. Our experimental results show that VACED-SIM exhibits higher accuracy and efficiency than MPI-SIM. In particular, for a target system with 1024 cores, the relative errors of VACED-SIM are less than 10% and the slowdowns are close to 1.

As supercomputers increase in size, the mean time between failures (MTBF) of a system becomes shorter, and the reliability problem of supercomputers becomes more and more serious. MPI is currently the de facto standard used to build high-performance applications, and researches on the fault tolerance methods of MPI are always hot topics. However, due to the characteristics of MPI programs, most current checkpointing methods for MPI programs need to modify the MPI library (even operating system), or implement a complicated protocol by logging lots of messages. In this paper, we carry forward the idea of Application-Level Checkpointing (ALC). Based on the general fact that programmers are familiar with the communication characteristics of applications, we have developed BC-ALC, a new portable blocking coordinated ALC for MPI programs. BC-ALC neither modifies the MPI library (even operating system) nor logs any message. It implements coordination only by the Barrier operations instead of any complicated protocol. Furthermore, in order to reduce the cost of fault-tolerance, we reduce the synchronization range of the barrier, and design WBC-ALC, a weak blocking coordinated ALC utilizing group synchronization instead of global synchronization based on the communication relationship between processes. We also propose a fault-tolerance framework developed on top of WBC-ALC and discuss an implementation of it. Experimental results on NPB3.3-MPI benchmarks validate BC-ALC and WBC-ALC, and show that compared with BC-ALC, the average coordination time and the average backup time of a single checkpoint in WBC-ALC are reduced by 44.5% and 5.7% respectively.