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Reciprocity, or the stochastic tendency for actors to form mutual relationships, is an essential characteristic of directed network data. Existing latent space approaches to modelling directed networks are severely limited by the assumption that reciprocity is homogeneous across the network. In this work, we introduce a new latent space model for directed networks that can model heterogeneous reciprocity patterns that arise from the actors' latent distances. Furthermore, existing conditionally edge‐independent latent space models are nested within the proposed model class, which allows for meaningful model comparisons. We introduce a Bayesian inference procedure to infer the model parameters using Hamiltonian Monte Carlo. Lastly, we use the proposed method to infer different reciprocity patterns in an advice network among lawyers, an information‐sharing network between employees at a manufacturing company and a friendship network between high school students. 

Processing-in-memory (PIM), where compute is moved closer to memory or data, has been explored to accelerate emerging workloads. Different PIM-based systems have been announced, each offering a unique microarchitectural organization of their compute units, ranging from fixed functional units to programmable general-purpose compute cores near memory. However, one fundamental limitation of PIM is that each compute unit can only access its local memory; access to “remote” memory must occur through the host CPU – potentially limiting application performance scalability. In this work, we first characterize the scalability of real PIM architectures using the UPMEM PIM system. We analyze how the overhead of communicating through the host (instead of providing direct communication between the PIM compute units) can become a bottleneck for collective communications that are commonly used in many workloads. To overcome this inter-PIM bank communication, we propose PIMnet – a PIM interconnection network for PIM banks that provides direct connectivity between compute units and removes the overhead of communicating through the host. PIMnet exploits bandwidth parallelism where communication across the different PIM bank/chips can occur in parallel to maximize communication performance. PIMnet also matches the DRAM packaging hierarchy with a multi-tier network architecture. Unlike traditional interconnection networks, PIMnet is a PIM controlled network where communication is managed by the PIM logic, optimizing collective communications and minimizing the hardware overhead of PIMnet. Our evaluation of PIMnet shows that it provides up to 85× speedup on collective communications and achieves a 11.8× improvement on real applications compared to the baseline PIM. 

Processing-in-memory (PIM), where the compute is moved closer to the memory or the data, has been widely explored to accelerate emerging workloads. Recently, different PIM-based systems have been announced by memory vendors to minimize data movement and improve performance as well as energy efficiency. One critical component of PIM is the large amount of compute parallelism provided across many PIM nodes'' or the compute units near the memory. In this work, we provide an extensive evaluation and analysis of real PIM systems based on UPMEM PIM. We show that while there are benefits of PIM, there are also scalability challenges and limitations as the number of PIM nodes increases. In particular, we show how collective communications that are commonly found in many kernels/workloads can be problematic for PIM systems. To evaluate the impact of collective communication in PIM architectures, we provide an in-depth analysis of two workloads on the UPMEM PIM system that utilize representative common collective communication patterns -- AllReduce and All-to-All communication. Specifically, we evaluate 1) embedding tables that are commonly used in recommendation systems that require AllReduce and 2) the Number Theoretic Transform (NTT) kernel which is a critical component of Fully Homomorphic Encryption (FHE) that requires All-to-All communication. We analyze the performance benefits of these workloads and show how they can be efficiently mapped to the PIM architecture through alternative data partitioning. However, since each PIM compute unit can only access its local memory, when communication is necessary between PIM nodes (or remote data is needed), communication between the compute units must be done through the host CPU, thereby severely hampering application performance. To increase the scalability (or applicability) of PIM to future workloads, we make the case for how future PIM architectures need efficient communication or interconnection networks between the PIM nodes that require both hardware and software support. 

Abstract Over the last fifty years, the use of nickel catalysts for facilitating organic transformations has skyrocketed. Nickel(0) sources act as useful precatalysts because they can enter a catalytic cycle through ligand exchange, without needing to undergo additional elementary steps. However, most Ni(0) precatalysts are synthesized with stoichiometric aluminum–hydride reductants, pyrophoric reagents that are not atom‐economical and must be used at cryogenic temperatures. Here, we demonstrate that Ni(II) salts can be reduced on preparative scale using electrolysis to yield a variety of Ni(0) and Ni(II) complexes that are widely used as precatalysts in organic synthesis, including bis(1,5‐cyclooctadiene)nickel(0) [Ni(COD)₂]. This method overcomes the reproducibility issues of previously reported methods by standardizing the procedure, such that it can be performed anywhere in a robust manner. It can be transitioned to large scale through an electrochemical recirculating flow process and extended to an in situ reduction protocol to generate catalytic amounts of Ni(0) for organic transformations. We anticipate that this work will accelerate adoption of preparative electrochemistry for the synthesis of low‐valent organometallic complexes in academia and industry. 

Abstract A flurry of recent research has centered on harnessing the power of nickel catalysis in organic synthesis. These efforts have been bolstered by contemporaneous development of well‐defined nickel (pre)catalysts with diverse structure and reactivity. In this report, we present ten different bench‐stable, 18‐electron, formally zero‐valent nickel–olefin complexes that are competent pre‐catalysts in various reactions. Our investigation includes preparations of novel, bench‐stable Ni(COD)(L) complexes (COD=1,5‐cyclooctadiene), in which L=quinone, cyclopentadienone, thiophene‐S‐oxide, and fulvene. Characterization by NMR, IR, single‐crystal X‐ray diffraction, cyclic voltammetry, thermogravimetric analysis, and natural bond orbital analysis sheds light on the structure, bonding, and properties of these complexes. Applications in an assortment of nickel‐catalyzed reactions underscore the complementary nature of the different pre‐catalysts within this toolkit.