We consider an efficient realization of the all-reduce operation with large data sizes in cluster environments, under the assumption that the reduce operator is associative and commutative. We derive a tight lower bound of the amount of data that must be communicated in order to complete this operation and propose a ring-based algorithm that only requires tree connectivity to achieve bandwidth optimality. Unlike the widely used butterfly-like all-reduce algorithm that incurs network contention in SMP/multi-core clusters, the proposed algorithm can achieve contention-free communication in almost all contemporary clusters including SMP/multi-core clusters and Ethernet switched clusters with multiple switches. We demonstrate that the proposed algorithm is more efficient than other algorithms on clusters with different nodal architectures and networking technologies when the data size is sufficiently large.

Two narrow‐bandgap block conjugated polymers with a (D1–A1)–(D2–A2) backbone architecture, namely PBDB‐T‐b‐PIDIC2T and PBDB‐T‐b‐PTY6, are designed and synthesized for single‐component organic solar cells (SCOSCs). Both polymers contain same donor polymer, PBDB‐T, but different polymerized nonfullerene molecule acceptors. Compared to all previously reported materials for SCOSCs, PBDB‐T‐b‐PIDIC2T and PBDB‐T‐b‐PTY6 exhibit narrower bandgap for better light harvesting. When incorporated into SCOSCs, the short‐circuit current density (Jsc) is significantly improved to over 15 mA cm−2, together with a record‐high power conversion efficiency (PCE) of 8.64%. Moreover, these block copolymers exhibit low energy loss due to high charge transfer (CT) states (Ect) plus small non‐radiative loss (0.26 eV), and improved stability under both ambient condition and continuous 80 °C thermal stresses for over 1000 h. Determination of the charge carrier dynamics and film morphology in these SCOSCs reveals increased carrier recombination, relative to binary bulk‐heterojunction devices, which is mainly due to reduced ordering of both donor and acceptor fragments. The close structural relationship between block polymers and their binary counterparts also provides an excellent framework to explore further molecular features that impact the photovoltaic performance and boost the state‐of‐the‐art efficiency of SCOSCs.

In order for collective communication routines to achieve high performance on different platforms, they must be able to adapt to the system architecture and use different algorithms for different situations. Current Message Passing Interface (MPI) implementations, such as MPICH and LAM/MPI, are not fully adaptable to the system architecture and are not able to achieve high performance on many platforms. In this paper, we present a system that produces efficient MPI collective communication routines. By automatically generating topology specific routines and using an empirical approach to select the best implementations, our system adapts to a given platform and constructs routines that are customized for the platform. The experimental results show that the tuned routines consistently achieve high performance on clusters with different network topologies.

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Abstract-In this paper we study the large-scale mixed-size placement problem where there is a significant size variation between big and small placeable objects (the ratio can be as large as 10,000). We develop a multi-level optimization algorithm, MPG-MS, for this problem which can efficiently handle both large-scale designs and large size variations. Compared with the recently published work [1] on large-scale mixed macro and standard cell placement benchmarks for wirelength minimization, our method can achieve 13% wirelength reduction on average with comparable runtime.