Towards an Adaptive Skeleton Framework for Performance Portability

The proliferation of widely available, but very different, parallel architectures makes the ability to deliver good parallel performance on a range of architectures, or performance portability, highly desirable. Irregularly-parallel problems, where the number and size of tasks is unpredictable, are particularly challenging and require dynamic coordination. The paper outlines a novel approach to delivering portable parallel performance for irregularly parallel programs. The approach combines declarative parallelism with JIT technology, dynamic scheduling, and dynamic transformation. We present the design of an adaptive skeleton library, with a task graph implementation, JIT trace costing, and adaptive transformations. We outline the architecture of the protoype adaptive skeleton execution framework in Pycket, describing tasks, serialisation, and the current scheduler.We report a preliminary evaluation of the prototype framework using 4 micro-benchmarks and a small case study on two NUMA servers (24 and 96 cores) and a small cluster (17 hosts, 272 cores). Key results include Pycket delivering good sequential performance e.g. almost as fast as C for some benchmarks; good absolute speedups on all architectures (up to 120 on 128 cores for sumEuler); and that the adaptive transformations do improve performance

Costing JIT Traces

Tracing JIT compilation generates units of compilation that are easy to analyse and are known to execute frequently. The AJITPar project aims to investigate whether the information in JIT traces can be used to make better scheduling decisions or perform code transformations to adapt the code for a specific parallel architecture. To achieve this goal, a cost model must be developed to estimate the execution time of an individual trace. This paper presents the design and implementation of a system for extracting JIT trace information from the Pycket JIT compiler. We define three increasingly parametric cost models for Pycket traces. We perform a search of the cost model parameter space using genetic algorithms to identify the best weightings for those parameters. We test the accuracy of these cost models for predicting the cost of individual traces on a set of loop-based micro-benchmarks. We also compare the accuracy of the cost models for predicting whole program execution time over the Pycket benchmark suite. Our results show that the weighted cost model using the weightings found from the genetic algorithm search has the best accuracy

UV spectra of iron-doped carbon clusters FeC_n n = 3-6

Electronic transitions of jet-cooled FeC$_n$ clusters ($n = 3 - 6$) were measured between 230 and 300 nm by a mass-resolved 1+1 resonant two-photon ionization technique. Rotational profiles were simulated based on previous calculations of ground state geometries and compared to experimental observations. Reasonable agreement is found for the planar fan-like structure of FeC$_3$. The FeC$_4$ data indicate a shorter distance between the Fe atom and the bent C$_4$ unit of the fan. The transitions are suggested to be $^{3}$A$_{2} \leftarrow ^{3}$B$_{1}$ for FeC$_3$ and $^{5}$A$_{1} \leftarrow ^{5}$A$_{1}$ for FeC$_4$. In contrast to the predicted C$_{\infty \text{v}}$ geometry, non-linear FeC$_5$ is apparently observed. Line width broadening prevents analysis of the FeC$_6$ spectrum.Comment: 6 pages, 5 figure

Strategies for increasing the applicability of biological network inference

The manipulation of cellular state has many promising applications, including stem cell biology and regenerative medicine, biofuel production, and stress resistant crop development. The construction of interaction maps promises to enhance our ability to engineer cellular behavior. Within the last 15 years, many methods have been developed to infer the structure of the gene regulatory interaction map from gene abundance snapshots provided by high-throughput experimental data. However, relatively little research has focused on using gene regulatory network models for the prediction and manipulation of cellular behavior. This dissertation examines and applies strategies to utilize the predictive power of gene network models to guide experimentation and engineering efforts. First, we developed methods to improve gene network models by integrating interaction evidence sources, in order to utilize the full predictive power of the models. Next, we explored the power of networks models to guide experimental efforts through inference and analysis of a regulatory network in the pathogenic fungus Cryptococcus neoformans. Finally, we develop a novel, network-guided algorithm to select genetic interventions for engineering transcriptional state. We apply this method to select intervention strains for improving biofuel production in a mixed glucose-xylose environment. The contributions in this dissertation provide the first thorough examination, systematic application, and quantitative evaluation of the utilization of network models for guiding cellular engineering

Electronic spectra of C6H+ and C6H 3 + in the gas phase

Measurement of the 3Π-3Π transition of C6H+ in the gas phase near 19486 cm−1 is reported. The experiment was carried out with a supersonic slit-jet expansion discharge using cavity ringdown absorption spectroscopy. Partly resolved P lines and observation of band heads permitted a rotational contour fit. Spectroscopic constants in the ground and excited-state were determined. The density of ions being sampled is merely 2×108 cm−3. Broadening of the spectral lines indicates the excited-state lifetime to be ≈100 ps. The electronic transition of HC6H 2 + at 26402 cm−1 assumed to be 1A1-X1A1 in C2v symmetry could not be rotationally resolve

Electronic spectra of C6H+ and C6H 3 + in the gas phase

Measurement of the 3Π-3Π transition of C6H+ in the gas phase near 19486 cm−1 is reported. The experiment was carried out with a supersonic slit-jet expansion discharge using cavity ringdown absorption spectroscopy. Partly resolved P lines and observation of band heads permitted a rotational contour fit. Spectroscopic constants in the ground and excited-state were determined. The density of ions being sampled is merely 2×108 cm−3. Broadening of the spectral lines indicates the excited-state lifetime to be ≈100 ps. The electronic transition of HC6H 2 + at 26402 cm−1 assumed to be 1A1-X1A1 in C2v symmetry could not be rotationally resolve