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In the present contribution, the following three cyclometallated Ir(III) complexes were theoretically investigated using density functional theory calculations to explain their different photophysical properties: [Ir(ppy)2(bpy)]+, where Hppy is 2-phenylpyridine and bpy is 2,2′-bipyridine, [Ir(ppy)2(pbpy)]+, where pbpy is 6-phenyl-2,2′-bipyridine, and [Ir(ppy)2(dpbpy)]+, where dpbpy is 6,6′-diphenyl-2,2′-bipyridine. Despite sharing the same molecular skeleton, with the only difference being the addition of one or two phenyl groups attached to the ancillary bpy ligand, the complexes show different emission quantum yields in CH2Cl2 solution (0.196, 0.049 and 0.036, respectively). Such a behavior was previously justified as a consequence of a different ability to non-radiatively decay through an axial metal-centered (MC) triplet state. In the present contribution, a new non-radiative decay path has been characterized to be mediated by the so-called equatorial MC states, in which an Ir–Nbpy bond is elongated instead of an Ir–Nppy bond as observed in the axial MC states. The decay path involving the equatorial MC states is more favorable than that associated with the axial MC states, and the different ability to decay through the former better explains the photoemission properties exhibited by the three complexes. [ABSTRACT FROM AUTHOR]

Precision spraying relies on the response of the spraying equipment to the features of the targeted canopy. PWM technology manages the flow rate using a set of electronically actuated solenoid valves to regulate flow rate at the nozzle level. Previous studies have found that PWM systems may deliver incorrect flow rates. The objective of the present study was to characterize the performance of a commercial blast sprayer modified with pulse-width-modulated nozzles under laboratory conditions, as a preliminary step before its further field validation. Four different duty cycles (25 percent, 50 percent, 75 percent and 100 percent) and four different pressures (400 kPa, 500 kPa, 600 kPa and 700 kPa) were combined to experimentally measure the flow rate of each nozzle. Results showed that the PWM nozzles mounted in the commercial blast sprayer, under static conditions, were capable of modulating flow rate according to the duty cycle. However, the reduction of flow rates for the tested duty cycles according to pressure was lower than the percentage expected. A good linear relation was found between the pressure registered by the control system feedback sensor and the pressure measured by a reference conventional manometer located after the pump. High-speed video recordings confirmed the accurate opening and closing of the nozzles according to the duty cycle; however, substantial pressure variations were found at nozzle level. Further research to establish the general suitability of PWM systems for regulating nozzle flow rates in blast sprayers without modifying the system pressure still remains to be addressed. [ABSTRACT FROM AUTHOR]

TensorFlow (TF) is usually combined with the Horovod (HVD) workload distribution package to obtain a parallel tool to train deep neural network on clusters of computers. HVD in turn utilizes a blocking Allreduce primitive to share information among processes, combined with a communication thread to overlap communication with computation. In this work, we perform a thorough experimental analysis to expose (1) the importance of selecting the best algorithm in MPI libraries to realize the Allreduce operation; and (2) the performance acceleration that can be attained when replacing a blocking Allreduce with its non-blocking counterpart (while maintaining the blocking behaviour via the appropriate synchronization mechanism). Furthermore, (3) we explore the benefits of applying pipelining to the communication exchange, demonstrating that these improvements carry over to distributed training via TF+HVD. Finally, (4) we show that pipelining can also boost performance for applications that make heavy use of other collectives, such as Broadcast and Reduce-Scatter. [ABSTRACT FROM AUTHOR]

We present a novel method for the QR factorization of large tall-and-skinny matrices that introduces an approximation technique for computing the Householder vectors. This approach is very competitive on a hybrid platform equipped with a graphics processor, with a performance advantage over the conventional factorization due to the reduced amount of data transfers between the graphics accelerator and the main memory of the host. Our experiments show that, for tall–skinny matrices, the new approach outperforms the code in MAGMA by a large margin, while it is very competitive for square matrices when the memory transfers and CPU computations are the bottleneck of the Householder QR factorization. [ABSTRACT FROM AUTHOR]

In a large number of scientific applications, the solution of sparse linear systems is the stage that concentrates most of the computational effort. This situation has motivated the study and development of several iterative solvers, among which preconditioned Krylov subspace methods occupy a place of privilege. In a previous effort, we developed a GPU-aware version of the GMRES method included in ILUPACK, a package of solvers distinguished by its inverse-based multilevel ILU preconditioner. In this work, we study the performance of our previous proposal and integrate several enhancements in order to mitigate its principal bottlenecks. The numerical evaluation shows that our novel proposal can reach important run-time reductions. [ABSTRACT FROM AUTHOR]

The Steered Response Power with Phase Transform (SRP-PHAT) algorithm is a well-known method for sound source localization due to its robust performance in noisy and reverberant environments. This algorithm is used in a large number of acoustic applications such as automatic camera steering systems, human–machine interaction, video gaming and audio surveillance. SPR-PHAT implementations require to handle a high number of signals coming from a microphone array and a huge search grid that influences the localization accuracy of the system. In this context, high performance in the localization process can only be achieved by using massively parallel computational resources. Different types of multi-core machines based either on multiple CPUs or on GPUs are commonly employed in diverse fields of science for accelerating a number of applications, mainly using OpenMP and CUDA as programming frameworks, respectively. This implies the development of multiple source codes which limits the portability and application possibilities. On the contrary, OpenCL has emerged as an open standard for parallel programming that is nowadays supported by a wide range of architectures. In this work, we evaluate an OpenCL-based implementations of the SRP-PHAT algorithm in two state-of-the-art CPU and GPU platforms. Results demonstrate that OpenCL achieves close-to-CUDA performance in GPU (considered as upper bound) and outperforms in most of the CPU configurations based on OpenMP. [ABSTRACT FROM AUTHOR]

Herein, we explore, from a theoretical perspective, the nonradiative photoinduced processes (charge separation and energy transfer) within a family of donor–acceptor supramolecular complexes based on the electron-donor truxene-tetrathiafulvalene (truxTTF) derivative and a series of curved fullerene fragments (buckybowls) of different shapes and sizes (C30H12, C32H12, and C38H14) as electron acceptors that successfully combine with truxTTF via non-covalent interactions. The resulting supramolecular complexes (truxTTF·C30H12, truxTTF·C32H12, and truxTTF·C38H14) undergo charge-separation processes upon photoexcitation through charge-transfer states involving the donor and acceptor units. Despite the not so different size of the buckybowls, they present noticeable differences in the charge-separation efficiency owing to a complex decay post-photoexcitation mechanism involving several low-lying excited states of different natures (local and charge-transfer excitations), all closely spaced in energy. In this intricate scenario, we have adopted a theoretical approach combining electronic structure calculations at (time-dependent) density functional theory, a multistate multifragment diabatization method, the Marcus–Levitch–Jortner semiclassical rate expression, and a kinetic model to estimate the charge separation rate constants of the supramolecular heterodimers. Our outcomes highlight that the efficiency of the photoinduced charge-separation process increases with the extension of the buckybowl backbone. The supramolecular heterodimer with the largest buckybowl (truxTTF·C38H14) displays multiple and efficient electron-transfer pathways, providing a global photoinduced charge separation in the ultrafast time scale in line with the experimental findings. The study reported indicates that modifications in the shape and size of buckybowl systems can give rise to attractive novel acceptors for potential photovoltaic applications. [ABSTRACT FROM AUTHOR]

We propose an approach to estimate the power consumption of algorithms, as a function of the frequency and number of cores, using only a very reduced set of real power measures. In addition, we also provide the formulation of a method to select the voltage-frequency scaling-concurrency throttling configurations that should be tested in order to obtain accurate estimations of the power dissipation. The power models and selection methodology are verified using two real scientific application: the stencil-based 3D MPDATA algorithm and the conjugate gradient (CG) method for sparse linear systems. MPDATA is a crucial component of the EULAG model, which is widely used in weather forecast simulations. The CG algorithm is the keystone for iterative solution of sparse symmetric positive definite linear systems via Krylov subspace methods. The reliability of the method is confirmed for a variety of ARM and Intel architectures, where the estimated results correspond to the real measured values with the average error being slightly below 5% in all cases. [ABSTRACT FROM AUTHOR]

Power-awareness in high-performance scientific computing has gained increased interest due to its non-negligible contributions to carbon-dioxide emissions and thus, to one of the main drivers of anthropocenic climate change. Although machine learning techniques are generally seen critical with respect to their energy footprint, due to the required expensive training phase, their clever combination with automatic tuning of sparse linear algebra tasks has excellent potential for energy savings. Here, the authors propose an asynchronous variant of the abstract Restricted Additive Schwarz method that introduces asynchronism between the sub-domains in order to eliminate the bulk synchronous execution pattern of the algorithm. [Extracted from the article]

Durch die Umsetzung neuer Beleuchtungskonzepte könnte die Verwertung von Energie deutlich effizienter gestaltet werden. Alle derzeit entwickelten Technologien beruhen auf elektrolumineszierenden Festkörpern und lassen sich allgemein als Festkörperbeleuchtung (solid-state lighting, SSL) einstufen. Die beiden wichtigsten Zweige der SSL-Technologie sind Leuchtdioden (LEDs) und organische Leuchtdioden (OLEDs), doch seit kurzem bilden auch leuchtende elektrochemische Zellen (LECs) eine Alternative, die als aktive Materialien entweder lumineszierende Polymere in Kombination mit ionischen Salzen oder lumineszierende ionische Spezies wie ionische Übergangsmetallkomplexe (iTMCs) enthalten. Cyclometallierte IrIII-Komplexe werden bei weitem am häufigsten als iTMCs in LECs verwendet. Hier zeigen wir, wie diese Komplexe hergestellt werden können, und wir diskutieren ihre einzigartigen elektronischen, photophysikalischen und photochemischen Eigenschaften. Schließlich werden die wichtigsten Fortschritte bezüglich Einschaltzeit, Stabilität, Effizienz und Farbe von iTMCs-LECs präsentiert. [ABSTRACT FROM AUTHOR]

Higher efficiency in the end-use of energy requires substantial progress in lighting concepts. All the technologies under development are based on solid-state electroluminescent materials and belong to the general area of solid-state lighting (SSL). The two main technologies being developed in SSL are light-emitting diodes (LEDs) and organic light-emitting diodes (OLEDs), but in recent years, light-emitting electrochemical cells (LECs) have emerged as an alternative option. The luminescent materials in LECs are either luminescent polymers together with ionic salts or ionic species, such as ionic transition-metal complexes (iTMCs). Cyclometalated complexes of IrIII are by far the most utilized class of iTMCs in LECs. Herein, we show how these complexes can be prepared and discuss their unique electronic, photophysical, and photochemical properties. Finally, the progress in the performance of iTMCs based LECs, in terms of turn-on time, stability, efficiency, and color is presented. [ABSTRACT FROM AUTHOR]

Light-emitting electrochemical cells (LECs) are solution-processable thin-film electroluminescent devices consisting of a luminescent material in an ionic environment. The simplest type of LEC is based on only one material, ionic transition-metal complexes (iTMCs). These materials are of interest for different scientific fields such as chemistry, physics, and technology as selected chemical modifications of iTMCs resulted in crucial breakthroughs for the performance of LECs. This short review highlights the different strategies used to design these compounds with the aim to enhance the performances of LECs. [ABSTRACT FROM AUTHOR]

With the emergence of thread-level parallelism as the primary means for continued performance improvement, the programmability issue has reemerged as an obstacle to the use of architectural advances. We argue that evolving legacy libraries for dense and banded linear algebra is not a viable solution due to constraints imposed by early design decisions. We propose a philosophy of abstraction and separation of concerns that provides a promising solution in this problem domain. The first abstraction, FLASH, allows algorithms to express computation with matrices consisting of contiguous blocks, facilitating algorithms-by-blocks. Operand descriptions are registered for a particular operation a priori by the library implementor. A runtime system, SuperMatrix, uses this information to identify data dependencies between suboperations, allowing them to be scheduled to threads out-of-order and executed in parallel. But not all classical algorithms in linear algebra lend themselves to conversion to algorithms-by-blocks. We show how our recently proposed LU factorization with incremental pivoting and a closely related algorithm-by-blocks for the QR factorization, both originally designed for out-of-core computation, overcome this difficulty. Anecdotal evidence regarding the development of routines with a core functionality demonstrates how the methodology supports high productivity while experimental results suggest that high performance is abundantly achievable. [ABSTRACT FROM AUTHOR]

We show how to compute an LU factonzation of a matrix when the factors of a leading principle submatrix are already known. The approach incorporates pivoting akin to partial pivoting, a strategy we call incremental pivoting. An implementation using the Formal Linear Algebra Methods Environment (FLAME) application programming interface (API) is described. Experimental results demonstrate practical numerical stability and high performance on an Intel Itanium2 processor-based server. [ABSTRACT FROM AUTHOR]

In this article, we present a number of Application Program Interfaces (APIs) for coding linear algebra algorithms. On the surface, these APIs for the MATLAB M-script and C programming languages appear to be simple, almost trivial, extensions of those languages. Yet with them, the task of programming and maintaining families of algorithms for a broad spectrum of linear algebra operations is greatly simplified. In combination with our Formal Linear Algebra Methods Environment (FLAME) approach to deriving such families of algorithms, dozens of algorithms for a single linear algebra operation can be derived, verified to be correct, implemented, and tested, often in a matter of minutes per algorithm. Since the algorithms are expressed in code much like they are explained in a classroom setting, these APIs become not just a tool for implementing libraries, but also a valuable tool for teaching the algorithms that are incorporated in the libraries. In combination with an extension of the Parallel Lin- ear Algebra Package (PLA.PACK) API, the approach presents a migratory path from algorithm to MATLAB implementation to high-performance sequential implementation to parallel implementation. Finally, the APIs are being used to create a repository of algorithms and implementations for linear algebra operations, the FLAME Interface REpository (FIRE), which already features hundreds of algorithms for dozens of commonly encountered linear algebra operations. [ABSTRACT FROM AUTHOR]

We discuss a parallel library of efficient algorithms for model reduction of large-scale systems with state-space dimension up to O(104). We survey the numerical algorithms underlying the implementation of the chosen model reduction methods. The approach considered here is based on state-space truncation of the system matrices and includes absolute and relative error methods for both stable and unstable systems. In contrast to serial implementations of these methods, we employ Newton-type iterative algorithms for the solution of the major computational tasks. Experimental results report the numerical accuracy and the parallel performance of our approach on a cluster of Intel Pentium II processors. [Copyright &y& Elsevier]

Model reduction is an area of fundamental importance in many modeling and control applications. In this paper we analyze the use of parallel computing in model reduction methods based on balanced truncation of large-scale dense systems. The methods require the computation of the Gramians of a linear-time invariant system. Using a sign function-based solver for computing full-rank factors of the Gramians yields some favorable computational aspects in the subsequent computation of the reduced-order model, particularly for non-minimal systems. As sign function-based computations only require efficient implementations of basic linear algebra operations readily available, e.g., in the BLAS, LAPACK, and ScaLAPACK, good performance of the resulting algorithms on parallel computers is to be expected. Our experimental results on a PC cluster show the performance and scalability of the parallel implementation. [ABSTRACT FROM AUTHOR]

In this paper we demonstrate the parallelism of the spectral division using the matrix sign function for the generalized nonsymmetric eigenproblem. We employ the so-called generalized Newton iterative scheme in order to compute the sign function of the matrix pair. A recent study showed a considerable reduction (by 75%) in the computational cost of this iteration, making this approach competitive when compared to the traditional QZ algorithm. The experimental results on an IBM SP3 multicomputer report the parallel performance (efficiency around 60-80%) and scalability of this approach. [ABSTRACT FROM AUTHOR]

A comprehensive investigation of two new molecular triads incorporating the diketopyrrolopyrrole unit into a quinoidized thienothiophene skeleton, which is further end‐capped with dicyanomethylene (DPP‐TT‐CN) or phenoxyl groups (DPP‐TT‐PhO), has been carried out. A combination of UV‐Vis‐NIR and infrared spectroelectrochemical techniques and cryogenic UV‐Vis‐NIR absorption spectroscopy supported by theoretical calculations has been used. The main result is the formation of similar H‐aggregates in the dimerization process of the neutral molecules and of the charged anionic species. The experimental absorption spectra of the aggregated species are accurately reproduced by quantum chemical calculations using the Spano's model, including excitonic coupling for the dimeric forms and full vibronic resolution of the absorption bands. The strong excitonic coupling taking place is key to understand the electronic structure of the dimeric species and has been instrumental to disentangle the type of H‐aggregation. This study is of relevance to get a better understanding of the molecular aggregation of organic π‐conjugated chromophores and is useful as a guideline for the refinement of the engineering of molecular materials for which supramolecular design is required. [ABSTRACT FROM AUTHOR]

We show an unexpected aggregation phenomenon of a long oligoyne (Py[16]) with 16 contiguous triple bonds and endcapped with bulky 3,5‐bi(3,5‐bis‐tert‐butylphenyl)pyridine groups. Aggregation of 1D π‐conjugated oligoyne chains is rare given the minimal π–π intermolecular interactions as well as its flexibility that works against self‐assembly. In dilute solutions, the reversible aggregation of Py[16] initiates at low temperature in the range of 140–180 K, and is not observed for shorter oligoynes in this series. Cryogenic UV/Vis electronic absorption spectra and vibrational Raman spectra with different laser wavelength lines tuning from in‐resonance to off‐resonance conditions have been used to extract the vibrational features characterizing the monomer and aggregate species. Theoretical calculations complement the spectroscopic findings. [ABSTRACT FROM AUTHOR]

We show an unexpected aggregation phenomenon of a long oligoyne (Py[16]) with 16 contiguous triple bonds and endcapped with bulky 3,5‐bi(3,5‐bis‐tert‐butylphenyl)pyridine groups. Aggregation of 1D π‐conjugated oligoyne chains is rare given the minimal π–π intermolecular interactions as well as its flexibility that works against self‐assembly. In dilute solutions, the reversible aggregation of Py[16] initiates at low temperature in the range of 140–180 K, and is not observed for shorter oligoynes in this series. Cryogenic UV/Vis electronic absorption spectra and vibrational Raman spectra with different laser wavelength lines tuning from in‐resonance to off‐resonance conditions have been used to extract the vibrational features characterizing the monomer and aggregate species. Theoretical calculations complement the spectroscopic findings. [ABSTRACT FROM AUTHOR]

In this paper we present several new fast and reliable algorithms for solving rank-deficient linear least squares problems by means of the complete orthogonal decomposition. Experimental comparison of our algorithms with the existing implementations in LAPACK on a wide range of platforms shows considerable performance improvements. Moreover, for full-rank matrices the performance of the new algorithm is very close to that of the fast method based on QR factorization, thus providing a valuable general tool for full-rank matrices, rank-deficient matrices, and those matrices with unknown rank. [ABSTRACT FROM AUTHOR]

We address the efficient realization of matrix multiplication (gemm), with application in the convolution operator for machine learning, for the RISC-V core present in the GreenWaves GAP8 processor. Our approach leverages BLIS (Basic Linear Algebra Instantiation Software) to develop an implementation that (1) re-organizes the gemm algorithm adapting its micro-kernel to exploit the hardware-supported dot product kernel in the GAP8; (2) explicitly orchestrates the data transfers across the hierarchy of scratchpad memories via DMA (direct memory access); and (3) operates with integer arithmetic. [ABSTRACT FROM AUTHOR]

The complex [Ir(ppy)2(pphen)][PF6] (Hppy = 2-phenylpyridine, pphen = 2-phenyl-1,10-phenanthroline) has been prepared and evaluated as an electroluminescent component for light-emitting electrochemical cells (LECs). Like in analogous LECs using bpy-based iridium(iii) complexes a significant enhancement of the device stability is observed. [ABSTRACT FROM AUTHOR]

The article focuses on the concept of supramolecular cage formation that can be extended to a phenylpyrazole-based iridium complex and its use in light-emitting electrochemical cells (LECs). It mentions the advantages of these cells over traditional organic light-emitting diodes (OLEDs), including simpler architectures. It notes the limited stability of LEC devices, which is said to primarily stem from the degradation of the ionic transition-metal complexes (iTMCs) used as the active component in the emissive layer.

7‐Azaindole has been integrated as building block with complementary N−H⋅⋅⋅N hydrogen bonding sites for the synthesis of a tetrahedral molecular tecton, namely tetra(α‐carbolin‐6‐yl)methane, TACM. The self‐assembly of this molecule results in a 3D hydrogen‐bonded organic framework (HOF). This supramolecular structure constitutes a crystalline microporous material with an extraordinary thermal and chemical robustness. Single crystal X‐ray diffraction reveals how the five‐fold catenation of diamonoid systems, stabilized by hydrogen bonds and π–π interactions, form an interpenetrated network with monodimensional channels. The structural features of the crystalline material are also observed by transmission electron microscopy (TEM). Additionally, the microporosity of the activated TACM‐HOF is characterized by gas sorption (N2, CO2, CH4 and H2) experiments performed at different pressures. A selective adsorption is observed for CO2 uptake and TACM‐HOF also presents a good adsorption capacity for H2 among supramolecular organic frameworks. [ABSTRACT FROM AUTHOR]

General matrix multiplication (gemm) is a fundamental kernel in scientific computing and current frameworks for deep learning. Modern realisations of gemm are mostly written in C, on top of a small, highly tuned micro-kernel that is usually encoded in assembly. The high performance realisation of gemm in linear algebra libraries in general include a single micro-kernel per architecture, usually implemented by an expert. In this paper, we explore a couple of paths to automatically generate gemm micro-kernels, either using C++ templates with vector intrinsics or high-level Python scripts that directly produce assembly code. Both solutions can integrate high performance software techniques, such as loop unrolling and software pipelining, accommodate any data type, and easily generate micro-kernels of any requested dimension. The performance of this solution is tested on three ARM-based cores and compared with state-of-the-art libraries for these processors: BLIS, OpenBLAS and ArmPL. The experimental results show that the auto-generation approach is highly competitive, mainly due to the possibility of adapting the micro-kernel to the problem dimensions. [ABSTRACT FROM AUTHOR]

We address the efficient implementation of the convolution operator on the GAP8 parallel ultra-low power platform (PULP), a heterogeneous multi-core processor equipped with a fabric controller (FC); a cluster of eight compute cores; and a four-level memory hierarchy with scratchpads instead of conventional, hardware-assisted cache memories. Our solution for this platform transforms the convolution into a general matrix–matrix multiplication (gemm) via the lowering approach, demonstrating that it is possible to attain reasonable performance on the GAP8 by carefully adapting techniques such as tiling and loop parallelism, which are mainstream in the multi-threaded, cache-aware realization of gemm. [ABSTRACT FROM AUTHOR]

Malleability is defined as the ability to vary the degree of parallelism at runtime, and is regarded as a means to improve core occupation on state-of-the-art multicore processors tshat contain tens of computational cores per socket. This property is especially interesting for applications consisting of irregular workloads and/or divergent executions paths. The integration of malleability in high-performance instances of the Basic Linear Algebra Subprograms (BLAS) is currently nonexistent, and, in consequence, applications relying on these computational kernels cannot benefit from this capability. In response to this scenario, in this paper we demonstrate that significant performance benefits can be gathered via the exploitation of malleability in a framework designed to implement portable and high-performance BLAS-like operations. For this purpose, we integrate malleability within the BLIS library, and provide an experimental evaluation of the result on three different practical use cases. [ABSTRACT FROM AUTHOR]

We explore the utilization of the Apache TVM open source framework to automatically generate a family of algorithms that follow the approach taken by popular linear algebra libraries, such as GotoBLAS2, BLIS, and OpenBLAS, to obtain high-performance blocked formulations of the general matrix multiplication (gemm). In addition, we fully automatize the generation process by also leveraging the Apache TVM framework to derive a complete variety of the processor-specific micro-kernels for gemm. This is in contrast with the convention in high-performance libraries, which hand-encode a single micro-kernel per architecture using Assembly code. In global, the combination of our TVM-generated blocked algorithms and micro-kernels for gemm (1) improves portability, maintainability, and, globally, streamlines the software life cycle; (2) provides high flexibility to easily tailor and optimize the solution to different data types, processor architectures, and matrix operand shapes, yielding performance on a par (or even superior for specific matrix shapes) with that of hand-tuned libraries; and (3) features a small memory footprint. [ABSTRACT FROM AUTHOR]

More than 10 years of research related to the development of efficient GPU routines for the sparse matrix-vector product (SpMV) have led to several realizations, each with its own strengths and weaknesses. In this work, we review some of the most relevant efforts on the subject, evaluate a few prominent routines that are publicly available using more than 3000 matrices from different applications, and apply machine learning techniques to anticipate which SpMV realization will perform best for each sparse matrix on a given parallel platform. Our numerical experiments confirm the methods offer such varied behaviors depending on the matrix structure that the identification of general rules to select the optimal method for a given matrix becomes extremely difficult, though some useful strategies (heuristics) can be defined. Using a machine learning approach, we show that it is possible to obtain unexpensive classifiers that predict the best method for a given sparse matrix with over 80% accuracy, demonstrating that this approach can deliver important reductions in both execution time and energy consumption. [ABSTRACT FROM AUTHOR]

The article focuses on the technological and economic impact of organic light emitters along with their benefits. Topics discussed include preparation of light-emitting fibers with coating of a steel wire with an electroluminescent material, use of light-emitting electrochemical cells as thin fibers, and preparation of the process of depositing the aligned carbon nanotube (CNT) for making fibers.

The unique self‐assembling features of N‐annulated perylene bisimides (PBIs) 1 and 2 are reported. The stability of the aggregates of diester 1, in which no H‐bonding interactions are operative, corroborates the significance of long‐range van der Waals and dipole–dipole electrostatic interactions in the construction of stable supramolecular assemblies. The incorporation of amide functional groups within the N‐annulated PBI in 2 stimulates pathway differentiation to achieve up to three J‐type aggregates and a fourth H‐type aggregate depending on the experimental conditions. The results presented demonstrate unprecedented levels of control over synthetic supramolecular self‐assembly and the rich differentiation that N‐annulated PBIs exhibit, opening the door to new, complex, functional supramolecular materials. [ABSTRACT FROM AUTHOR]

The unique self‐assembling features of N‐annulated perylene bisimides (PBIs) 1 and 2 are reported. The stability of the aggregates of diester 1, in which no H‐bonding interactions are operative, corroborates the significance of long‐range van der Waals and dipole–dipole electrostatic interactions in the construction of stable supramolecular assemblies. The incorporation of amide functional groups within the N‐annulated PBI in 2 stimulates pathway differentiation to achieve up to three J‐type aggregates and a fourth H‐type aggregate depending on the experimental conditions. The results presented demonstrate unprecedented levels of control over synthetic supramolecular self‐assembly and the rich differentiation that N‐annulated PBIs exhibit, opening the door to new, complex, functional supramolecular materials. [ABSTRACT FROM AUTHOR]

Malleability is a property of certain applications (or tasks) that, given an external request or autonomously, can accommodate a dynamic modification of the degree of parallelism being exploited at runtime. Malleability improves resource usage (core occupation) on modern multicore architectures for applications that exhibit irregular and divergent execution paths and heavily depend on the underlying library performance to attain high performance. The integration of malleability within high-performance instances of the Basic Linear Algebra Subprograms (BLAS) is nonexistent, and, in addition, it is difficult to attain given the rigidity of current application programming interfaces (APIs). In this paper, we overcome these issues presenting the integration of a malleability mechanism within BLIS, a high-performance and portable framework to implement BLAS-like operations. For this purpose, we leverage low-level (yet simple) APIs to integrate on-demand malleability across all Level-3 BLAS routines, and we demonstrate the performance benefits of this approach by means of a higher-level dense matrix operation: the LU factorization with partial pivoting and look-ahead. [ABSTRACT FROM AUTHOR]

The low-lying electronic excited states of thieno[3,4-b]pyrazine have been studied using the multiconfigurational second-order perturbation CASPT2 theory with extended atomic natural orbital basis sets. The CASPT2 results allow for a full interpretation of the electronic absorption and emission spectra and provide valuable information for the rationalization of the experimental data. The nature, position, and intensity of the spectral bands have been analyzed in detail. A preliminary comparative study of the ground-state geometry of thieno[3,4-b]pyrazine has been performed at the coupled cluster single and doubles and density functional theory levels using a variety of correlation-consistent basis sets. Thieno[3,4-b]pyrazine exhibits a polyene-like structure in the ground state due to the bond localization in the pyrazine moiety. An aromatization of the pyrazine unit is predicted for the lowest-energy electronic excited states. [ABSTRACT FROM AUTHOR]

A Global Navigation Satellite System (GNSS) is widely used today for both positioning and timing purposes. Many distinct receiver chips are available as Application-Specific Integrated Circuit (ASIC)s off-the-shelf, each tailored to the requirements of various applications. These chips deliver good performance and low energy consumption but offer customers little-to-no transparency about their internal features. This prevents modification, research in GNSS processing chain enhancement (e.g., application of Approximate Computing (AxC) techniques), and design space exploration to find the optimal receiver for a use case. In this paper, we review the GNSS processing chain using SyDR, our open-source GNSS Software-Defined Radio (SDR) designed for algorithm benchmarking, and highlight the limitations of a software-only environment. In return, we propose an evolution to our system, called Hard SyDR to become closer to the hardware layer and access new Key Performance Indicator (KPI)s, such as power/energy consumption and resource utilization. We use High-Level Synthesis (HLS) and the PYNQ platform to ease our development process and provide an overview of their advantages/limitations in our project. Finally, we evaluate the foreseen developments, including how this work can serve as the foundation for an exploration of AxC techniques in future low-power GNSS receivers. [ABSTRACT FROM AUTHOR]

We present a reliable and efficient FPGA implementation of a procedure for the computation of the noise estimation matrix, a key stage for subspace identification of hyperspectral images. Our hardware realization is based on numerically stable orthogonal transformations, avoids the numerical difficulties of the normal equations method for the solution of linear least squares problems (LLS), and exploits the special relations between coupled LLS problems arising in the hyperspectral image. Our modular implementation decomposes the QR factorization that comprises a significant part of the cost into a sequence of suboperations, which can be efficiently computed on an FPGA. [ABSTRACT FROM AUTHOR]

The electronic spectrum of bithiophene in the energy range up to 6.0 eV has been studied using multiconfigurational second order perturbation theory (CASPT2) and a basis set of ANO type, with split valence quality and including polarization functions on all heavy atoms. Calculations were performed at a planar (trans) and twisted geometry. The calculated ordering of the excited singlet states is 1Bu, 1Bu, 1Ag, 1Ag, and 1Bu with 0–0 transition energies: 3.88, 4.15, 4.40, 4.71, and 5.53 eV, respectively. The first Rydberg transition (3s) has been found at 5.27 eV. The results have been used in aiding the interpretation of the experimental spectra, and in cases where a direct comparison is possible there is agreement between theory and experiment. © 1995 American Institute of Physics. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including parallel linear algebra algorithms, parallelization of applications, and tools for parallel programming.

The synthesis and characterization of a new Co(II) spin‐crossover (SCO) complex based on 4′‐(4‐carboxyphenyl)−2,2′:6′,2″‐terpyridine ligand are reported. This complex can be successfully grafted on silver surface maintaining the SCO behavior. Thus, atomic force microscopy (AFM), matrix assisted laser desorption ionization – time‐of‐flight mass spectrometry (MALDI‐TOF MS), Raman spectroscopy, and XPS measurements, upon surface deposition, evidence the formation of a monolayer of intact molecules grafted through carboxylate groups to the Ag surface. Three different techniques: Raman spectroscopy, X‐ray photoelectron spectroscopy (XPS), and X‐ray absorption spectroscopy (XAS), supported by first‐principles calculations, confirm that the deposited molecules undergo a gradual spin transition with temperature. This phenomenon is unprecedented for a monolayer of molecules directly grafted onto a metallic surface from solution. [ABSTRACT FROM AUTHOR]

Materials based on organic chromophores and lanthanides able to transform low‐energy photons, specifically near‐infrared (NIR) photons, into higher energy photons to eventually lead to long‐lived sensitized emission of the dye are highly desirable. Cooperative sensitization (CS) upconversion has only been accomplished for lanthanide‐based clusters. We used here the eosin Y (EOS) dianion and Yb3+ (EOS‐Yb), and demonstrate the efficient CS emission of the dye after NIR excitation. Remarkably, the EOS dianion emission exhibits a nearly linear dependence on the EOS‐Yb concentration and a quadratic dependence on the laser power density. The emission is non‐sensitive to oxygen and its lifetime lasts about 1.76 μs and 12 μs in DMSO and DMSO‐d6, respectively. Moreover, the effect of temperature (293–363 K range) on the EOS‐Yb 1H NMR spectroscopic shifts demonstrates the reversible dynamic nature of the material. [ABSTRACT FROM AUTHOR]

Adaptive workloads can change on–the–fly the configuration of their jobs, in terms of number of processes. To carry out these job reconfigurations, we have designed a methodology which enables a job to communicate with the resource manager and, through the runtime, to change its number of MPI ranks. The collaboration between both the workload manager—aware of the queue of jobs and the resources allocation—and the parallel runtime—able to transparently handle the processes and the program data—is crucial for our throughput-aware malleability methodology. Hence, when a job triggers a reconfiguration, the resource manager will check the cluster status and return the appropriate action: i) expand , if there are spare resources; ii) shrink , if queued jobs can be initiated; or iii) none , if no change can improve the global productivity. In this paper, we describe the internals of our framework and demonstrate how it reduces the global workload completion time along with providing a more efficient usage of the underlying resources. For this purpose, we present a thorough study of the adaptive workloads processing by showing the detailed behavior of our framework in representative experiments. [ABSTRACT FROM AUTHOR]

We analyze the benefits of look-ahead in the parallel execution of the LU factorization with partial pivoting (LUpp) in two distinct “asymmetric” multicore scenarios. The first one corresponds to an actual hardware-asymmetric architecture such as the Samsung Exynos 5422 system-on-chip (SoC), equipped with an ARM big.LITTLE processor consisting of a quad-core Cortex-A15 cluster plus a quad-core Cortex-A7 cluster. For this scenario, we propose a careful mapping of the different types of tasks appearing in LUpp to the computational resources, in order to produce an efficient architecture-aware exploitation of the computational resources integrated in this SoC. The second asymmetric configuration appears in a hardware-symmetric multicore architecture where the cores can individually operate at a different frequency levels. In this scenario, we show how to employ the frequency slack to accelerate the tasks in the critical path of LUpp in order to produce a faster global execution as well as a lower energy consumption. [ABSTRACT FROM AUTHOR]

Near Threshold Voltage (NTV) computing has been recently proposed as a technique to save energy, at the cost of incurring higher error rates including, among others, Silent Data Corruption (SDC). In this paper, we evaluate the energy efficiency of dense linear algebra routines using several low-power multicore processors and we analyze whether the potential energy reduction achieved when scaling the processor to operate at a low voltage compensates the cost of integrating a fault tolerance mechanism that tackles SDC. Our study targets algorithmic-based fault-tolerant versions of the dense matrix-vector and matrix(-matrix) multiplication kernels ( gemv and gemm , respectively), using the BLIS framework, as well as an implementation of the LU factorization with partial pivoting built on top of gemm . Furthermore, we tailor the study for a number of representative 32-bit and 64-bit multicore processors from ARM that were specifically designed for energy efficiency. [ABSTRACT FROM AUTHOR]

A theoretical density functional theory study has been performed on a family of cationic iridium(III) complexes of the form [Ir(C^N) 2 (dtBubpy)] + (dtBubpy = 4,4′-di-tert-butyl-2,2′-bipyridine), that incorporate 2-phenylpyridine ( 1 , 2 ) and 1-phenylpyrazole ( 3 , 4 ) cyclometallating C^N ligands functionalized with SF 5 groups. The goal is to investigate the effect that the inclusion of SF 5 groups in meta ( 1 , 3 ) and para position ( 2 , 4 ) with respect to the Ir–C bond has on the electronic nature of the emitting triplet state and the emission wavelength. The attachment of the electron-withdrawing groups induces the stabilization of the molecular orbitals localized on the C^N ligands and, in particular, of the highest-occupied molecular orbital (HOMO). This stabilization enlarges the energy gap between the HOMO and the lowest-unoccupied molecular orbital (LUMO), and shifts to higher energies the metal-to-ligand charge transfer (MLCT) triplet described by the HOMO → LUMO excitation. As a consequence, a triplet state of ligand-centered (LC) nature becomes the lowest-energy triplet excited state for all the four complexes. For complexes 1 and 2 , the state is centered on the C^N ligands ( 3 LC C^N ) and the introduction of the SF 5 groups in para causes a greater effect than their insertion in meta . Substitution of the pyridine ring by a pyrazole ring in complexes 3 and 4 destabilizes the 3 LC C^N states and the lowest-energy triplet involves the diimine N^N ligand ( 3 LC N^N ). Theoretical calculations therefore predict that the electronic nature of the lowest-lying triplet drastically changes in passing from the unsubstituted complex ( 3 MLCT) to complexes 1 and 2 ( 3 LC C^N ) and to complexes 3 and 4 ( 3 LC N^N ). These changes help to rationalize the aspect of the emission spectra and the shift to the blue of the emission wavelength. The appearance of low energy 3 LC triplets centered on the ancillary ligand, whose energy is hardly affected by changes in the C^N ligands structure, constitutes a limit to blue-shift the phosphorescence emission in this kind of complexes. [ABSTRACT FROM AUTHOR]

Understanding how molecular systems self-assemble to form well-organized superstructures governed by noncovalent interactions is essential in the field of supramolecular chemistry. In the nanoscience context, the self-assembly of different carbon-based nanoforms (fullerenes, carbon nanotubes and graphene) with, in general, electron-donor molecular systems, has received increasing attention as a means of generating potential candidates for technological applications. In these carbon-based systems, a deep characterization of the supramolecular organization is crucial to establish an intimate relation between supramolecular structure and functionality. Detailed structural information on the self-assembly of these carbon-based nanoforms is however not always accessible from experimental techniques. In this regard, quantum chemistry has demonstrated to be key to gain a deep insight into the supramolecular organization of molecular systems of high interest. In this review, we intend to highlight the fundamental role that quantum-chemical calculations can play to understand the supramolecular self-assembly of carbon-based nanoforms through a limited selection of supramolecular assemblies involving fullerene, fullerene fragments, nanotubes and graphene with several electron-rich π-conjugated systems. [ABSTRACT FROM AUTHOR]

We take a step forward towards developing high-performance codes for the convolution operator, based on the Winograd algorithm, that are easy to customise for general-purpose processor architectures. In our approach, augmenting the portability of the solution is achieved via the introduction of vector instructions from Intel SSE/AVX2/AVX512 and ARM NEON/SVE to exploit the single-instruction multiple-data capabilities of current processors as well as OpenMP pragmas to exploit multi-threaded parallelism. While this comes at the cost of sacrificing a fraction of the computational performance, our experimental results on three distinct processors, with Intel Xeon Skylake, ARM Cortex A57 and Fujitsu A64FX processors, show that the impact is affordable and still renders a Winograd-based solution that is competitive when compared with the lowering gemm-based convolution. [ABSTRACT FROM AUTHOR]

In this work, we present scaled variants of the DLPNO-CCSD(T) method, dubbed as (LS)DLPNO-CCSD(T) and (NS)DLPNO-CCSD(T), to obtain accurate interaction energies in supramolecular complexes governed by noncovalent interactions. The novel scaled schemes are based on the linear combination of the DLPNO-CCSD(T) correlation energies calculated with the standard (LoosePNO and NormalPNO) and modified (Loose2PNO and Normal2PNO) DLPNO-CCSD(T) accuracy levels. The scaled DLPNO-CCSD(T) variants provide nearly TightPNO accuracy, which is essential for the quantification of weak noncovalent interactions, with a noticeable saving in computational cost. Importantly, the accuracy of the proposed schemes is preserved irrespective of the nature and strength of the supramolecular interaction. The (LS)DLPNO-CCSD(T) and (NS)DLPNO-CCSD(T) protocols have been used to study in depth the role of the CH-π versus π-π interactions in the supramolecular complex formed by the electron-donor truxene-tetrathiafulvalene (truxTTF) and the electron-acceptor hemifullerene (C30H12). (NS)DLPNO-CCSD(T)/CBS calculations clearly reveal the higher stability of staggered (dominated by CH-π interactions) versus bowl-in-bowl (dominated by π-π interactions) arrangements in the truxTTF•C30H12 heterodimer. Hemifullerene and similar carbon-based buckybowls are therefore expected to self-assemble with donor compounds in a richer way other than the typical concave-convex π-π arrangement found in fullerene-based aggregates. © 2017 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]