#Amd firestream 9370 benchmark generator#
#Amd firestream 9370 benchmark verification#

Over the years, the improvement of security, privacy and service quality in information exchange has facilitated the creation of large networks for scientific communication, which in turn have allowed the incorporation of infrastructures for high-performance computing into the improvement of science. When first implemented, the use of supercomputers occurred mainly in the military field, at which point they were very rudimentary, offering little possibility of communication networking.

Supercomputing involves not only the development and provision of infrastructures of large capacity for the scientific and business community, but a new way to manage the tasks of research, development and innovation, making it necessary to use high-capacity communication networks that allow the transfer of a great volume of data between research and high-performance computing facilities. The optimization results in 1.14 times faster execution on SX-ACE and 1.81 times faster execution on LX 406-Re2. By applying our approaches to the implementation, the memory usage of the plasmonics simulation application can be reduced up to nearly 1/71 of the original, and its execution can be possible on a single node of a distributed parallel system with smaller memory capacity. To validate the effectiveness of our approaches, a plasmonics simulation application is evaluated on vector platforms NEC SX-ACE, NEC SX-9, and Intel Xeon based platform NEC LX 406-Re2. Our approaches include memory optimizations through memory footprint controlling, restructuring of data structures for active elements, redundant data structure elimination through combined calculations and optimized re-calculation of data. In this paper, we discuss a set of approaches to optimization of the memory access behavior of the applications, which enable their executions with improved performance on the recent HPC systems. To fully exploit the potential of the recent HPC systems, and to meet the increasing demand for large memory, it is necessary to optimize practical scientific and engineering applications, considering not only the parallelism of the applications, but also the limitations of the memory subsystems of the HPC systems. The bytes per flop (B/F), which is a ratio of the memory bandwidth to the flop/s, for the HPC systems have been reduced with the evolution of the HPC systems. Most recent HPC systems adopt a parallel processing architecture, where the computational capability of the processors is increasing, however, the performance of the memory system is constrained. Since recent scientific and engineering simulations require heavy computations with large volumes of data, High-performance Computing (HPC) systems need a high computational capability with a large memory capacity. An example which illustrates the application of the mentioned methods is described.

#Amd firestream 9370 benchmark verification#

The first one automatically generates the replacement operation in ACL2 language, the second one automatically generates auxiliary lemmas which allow to prove the obtained verification conditions in ACL2 successfully in automatic mode. To prove verification conditions automatically in ACL2, two algorithms were developed and implemented.

#Amd firestream 9370 benchmark generator#

This rule was implemented in verification conditions generator which is a part of the automated system of C-light program verification. The method contains the inference rule for iterations without loop invariants. This extension includes the verification method of iterations over changeable arrays possibly with loop exit in C-light programs. It extends the mixed axiomatic semantics method suggested for C-light program verification. This work represents the further development of this method.

This operation expresses loop effect in a symbolic form and allows to introduce an inference rule which uses no invariants in axiomatic semantics. Its idea is to represent a loop body in a form of special replacement operation under certain constraints. An alternative is the symbolic method of loop invariant elimination suggested by V.A. As a rule, the methods of invariant synthesis are heuristic ones. During deductive verification of programs written in imperative languages, the generation and proof of verification conditions corresponding to loops can cause difficulties, because each one must be provided with an invariant whose construction is often a challenge.