This information can then be used to generate a fine-grained energy-efficient schedule for execution of the computations – as well as a schedule of frequency changes on a per-core basis – while satisfying performance requirements of computations.
With the increasing requirement of computation and data amount in embedded multimedia applications, stream architectures are exploited to accelerate the multimedia processing.
A key component of DREAM-MCP is the Reasoner, which takes as parameters the resource requirements of a computation and its deadline, and decides whether the computation can be accommodated using resources available in the system.
Regardless of the limited sample set, the quantitative prediction model can give consideration to both universality and generalization to meet the requirements of engineering computation application.
Despite advancements in numerical schemes and high-performance computing, the requirements of iterative computations and fine grids hinder further extension of the RE to multi-dimensional and large-scale applications.
Attempts to use conventional techniques have encountered insurmountable difficulties, due to excessive CPU time requirements of the computations involved.
The data parallelism and flexible on-chip communications are essential to meet the high-performance requirements of the computations being performed.
We define the state of the system as S = ( Θ, ρ, t ), where Θ is a set of resource terms, representing future available resources in the system, as of time t; ρ represents the resource requirements of the computations that are accommodated by the system at time t; and t is the point in time when the system's state is being captured.
Other software and algorithms [ 25- 27], for example, could be used to identify extreme pathways, which would certainly change the time and memory requirements of these computations.
RAxML-Light is a production-level tool for phylogenetic inference on supercomputers that implements new approaches for handling load imbalance, checkpointing and reducing the RAM requirements of likelihood computations.
