483,302 research outputs found
Refined Genetic Algorithms for Polypeptide Structure Prediction
Accurate and reliable prediction of macromolecular structures has eluded researchers for nearly 40 years. Prediction via energy minimization assumes the native conformation has the globally minimal energy potential. An exhaustive search is impossible since for molecules of normal size, the size of the search space exceeds the size of the universe. Domain knowledge sources, such as the Brookhaven PDB can be mined for constraints to limit the search space. Genetic algorithms (GAs) are stochastic, population based, search algorithms of polynomial (P) time complexity that can produce semi-optimal solutions for problems of nondeterministic polynomial (NP) time complexity such as PSP. Three refined GAs are presented: A farming model parallel hybrid GA (PHGA) preserves the effectiveness of the serial algorithm with substantial speed up. Portability across distributed and MPP platforms is accomplished with the Message Passing Interface (MPI) communications standard. A Real-valved GA system, real-valued Genetic Algorithm, Limited by constraints (REGAL), exploiting domain knowledge. Experiments with the pentapeptide Met-enkephalin have identified conformers with lower energies (CHARMM) than the accepted optimal conformer (Scheraga, et al), -31.98 vs -28.96 kcals/mol. Analysis of exogenous parameters yields additional insight into performance. A parallel version (Para-REGAL), an island model modified to allow different active constraints in the distributed subpopulations and novel concepts of Probability of Migration and Probability of Complete Migration
CAIR: Using Formal Languages to Study Routing, Leaking, and Interception in BGP
The Internet routing protocol BGP expresses topological reachability and
policy-based decisions simultaneously in path vectors. A complete view on the
Internet backbone routing is given by the collection of all valid routes, which
is infeasible to obtain due to information hiding of BGP, the lack of
omnipresent collection points, and data complexity. Commonly, graph-based data
models are used to represent the Internet topology from a given set of BGP
routing tables but fall short of explaining policy contexts. As a consequence,
routing anomalies such as route leaks and interception attacks cannot be
explained with graphs.
In this paper, we use formal languages to represent the global routing system
in a rigorous model. Our CAIR framework translates BGP announcements into a
finite route language that allows for the incremental construction of minimal
route automata. CAIR preserves route diversity, is highly efficient, and
well-suited to monitor BGP path changes in real-time. We formally derive
implementable search patterns for route leaks and interception attacks. In
contrast to the state-of-the-art, we can detect these incidents. In practical
experiments, we analyze public BGP data over the last seven years
Accuracy Boosters: Epoch-Driven Mixed-Mantissa Block Floating-Point for DNN Training
The unprecedented growth in DNN model complexity, size and the amount of
training data have led to a commensurate increase in demand for computing and a
search for minimal encoding. Recent research advocates Hybrid Block
Floating-Point (HBFP) as a technique that minimizes silicon provisioning in
accelerators by converting the majority of arithmetic operations in training to
8-bit fixed-point. In this paper, we perform a full-scale exploration of the
HBFP design space including minimal mantissa encoding, varying block sizes, and
mixed mantissa bit-width across layers and epochs. We propose Accuracy
Boosters, an epoch-driven mixed-mantissa HBFP that uses 6-bit mantissa only in
the last epoch and converts of all arithmetic operations in training
to 4-bit mantissas. Accuracy Boosters enable reducing silicon provisioning for
an HBFP training accelerator by as compared to FP32, while
preserving or outperforming FP32 accuracy
Shift-Symmetric Configurations in Two-Dimensional Cellular Automata: Irreversibility, Insolvability, and Enumeration
The search for symmetry as an unusual yet profoundly appealing phenomenon,
and the origin of regular, repeating configuration patterns have long been a
central focus of complexity science and physics. To better grasp and understand
symmetry of configurations in decentralized toroidal architectures, we employ
group-theoretic methods, which allow us to identify and enumerate these inputs,
and argue about irreversible system behaviors with undesired effects on many
computational problems. The concept of so-called configuration shift-symmetry
is applied to two-dimensional cellular automata as an ideal model of
computation. Regardless of the transition function, the results show the
universal insolvability of crucial distributed tasks, such as leader election,
pattern recognition, hashing, and encryption. By using compact enumeration
formulas and bounding the number of shift-symmetric configurations for a given
lattice size, we efficiently calculate the probability of a configuration being
shift-symmetric for a uniform or density-uniform distribution. Further, we
devise an algorithm detecting the presence of shift-symmetry in a
configuration.
Given the resource constraints, the enumeration and probability formulas can
directly help to lower the minimal expected error and provide recommendations
for system's size and initialization. Besides cellular automata, the
shift-symmetry analysis can be used to study the non-linear behavior in various
synchronous rule-based systems that include inference engines, Boolean
networks, neural networks, and systolic arrays.Comment: 22 pages, 9 figures, 2 appendice
On the Complexity of Computing Minimal Unsatisfiable LTL formulas
We show that (1) the Minimal False QCNF search-problem (MF-search) and the
Minimal Unsatisfiable LTL formula search problem (MU-search) are FPSPACE
complete because of the very expressive power of QBF/LTL, (2) we extend the
PSPACE-hardness of the MF decision problem to the MU decision problem. As a
consequence, we deduce a positive answer to the open question of PSPACE
hardness of the inherent Vacuity Checking problem. We even show that the
Inherent Non Vacuous formula search problem is also FPSPACE-complete.Comment: Minimal unsatisfiable cores For LTL causes inherent vacuity checking
redundancy coverag
- …