41,102 research outputs found
Liquid rocket metal tanks and tank components
Significant guidelines are presented for the successful design of aerospace tanks and tank components, such as expulsion devices, standpipes, and baffles. The state of the art is reviewed, and the design criteria are presented along with recommended practices. Design monographs are listed
Bellman Error Based Feature Generation using Random Projections on Sparse Spaces
We address the problem of automatic generation of features for value function
approximation. Bellman Error Basis Functions (BEBFs) have been shown to improve
the error of policy evaluation with function approximation, with a convergence
rate similar to that of value iteration. We propose a simple, fast and robust
algorithm based on random projections to generate BEBFs for sparse feature
spaces. We provide a finite sample analysis of the proposed method, and prove
that projections logarithmic in the dimension of the original space are enough
to guarantee contraction in the error. Empirical results demonstrate the
strength of this method
Beyond Reuse Distance Analysis: Dynamic Analysis for Characterization of Data Locality Potential
Emerging computer architectures will feature drastically decreased flops/byte
(ratio of peak processing rate to memory bandwidth) as highlighted by recent
studies on Exascale architectural trends. Further, flops are getting cheaper
while the energy cost of data movement is increasingly dominant. The
understanding and characterization of data locality properties of computations
is critical in order to guide efforts to enhance data locality. Reuse distance
analysis of memory address traces is a valuable tool to perform data locality
characterization of programs. A single reuse distance analysis can be used to
estimate the number of cache misses in a fully associative LRU cache of any
size, thereby providing estimates on the minimum bandwidth requirements at
different levels of the memory hierarchy to avoid being bandwidth bound.
However, such an analysis only holds for the particular execution order that
produced the trace. It cannot estimate potential improvement in data locality
through dependence preserving transformations that change the execution
schedule of the operations in the computation. In this article, we develop a
novel dynamic analysis approach to characterize the inherent locality
properties of a computation and thereby assess the potential for data locality
enhancement via dependence preserving transformations. The execution trace of a
code is analyzed to extract a computational directed acyclic graph (CDAG) of
the data dependences. The CDAG is then partitioned into convex subsets, and the
convex partitioning is used to reorder the operations in the execution trace to
enhance data locality. The approach enables us to go beyond reuse distance
analysis of a single specific order of execution of the operations of a
computation in characterization of its data locality properties. It can serve a
valuable role in identifying promising code regions for manual transformation,
as well as assessing the effectiveness of compiler transformations for data
locality enhancement. We demonstrate the effectiveness of the approach using a
number of benchmarks, including case studies where the potential shown by the
analysis is exploited to achieve lower data movement costs and better
performance.Comment: Transaction on Architecture and Code Optimization (2014
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