RapidChiplet: A Toolchain for Rapid Design Space Exploration of Chiplet Architectures

Chiplet architectures are a promising paradigm to overcome the scaling challenges of monolithic chips. Chiplets offer heterogeneity, modularity, and cost-effectiveness. The design space of chiplet architectures is huge as there are many degrees of freedom such as the number, size and placement of chiplets, the topology of the inter-chiplet interconnect and many more. Existing tools for cost and performance prediction are often too slow to explore this design space. We present RapidChiplet, a fast, open-source toolchain to predict latency and throughput of the inter-chiplet interconnect, as well as a chip's manufacturing cost and thermal stability

HexaMesh: Scaling to Hundreds of Chiplets with an Optimized Chiplet Arrangement

2.5D integration is an important technique to tackle the growing cost of manufacturing chips in advanced technology nodes. This poses the challenge of providing high-performance inter-chiplet interconnects (ICIs). As the number of chiplets grows to tens or hundreds, it becomes infeasible to hand-optimize their arrangement in a way that maximizes the ICI performance. In this paper, we propose HexaMesh, an arrangement of chiplets that outperforms a grid arrangement both in theory (network diameter reduced by 42%; bisection bandwidth improved by 130%) and in practice (latency reduced by 19%; throughput improved by 34%). MexaMesh enables large-scale chiplet designs with high-performance ICIs

Sparse Hamming Graph: A Customizable Network-on-Chip Topology

Chips with hundreds to thousands of cores require scalable networks-on-chip (NoCs). Customization of the NoC topology is necessary to reach the diverse design goals of different chips. We introduce sparse Hamming graph, a novel NoC topology with an adjustable costperformance trade-off that is based on four NoC topology design principles we identified. To efficiently customize this topology, we develop a toolchain that leverages approximate floorplanning and link routing to deliver fast and accurate cost and performance predictions. We demonstrate how to use our methodology to achieve desired cost-performance trade-offs while outperforming established topologies in cost, performance, or both

Neural Graph Databases

Graph databases (GDBs) enable processing and analysis of unstructured, complex, rich, and usually vast graph datasets. Despite the large significance of GDBs in both academia and industry, little effort has been made into integrating them with the predictive power of graph neural networks (GNNs). In this work, we show how to seamlessly combine nearly any GNN model with the computational capabilities of GDBs. For this, we observe that the majority of these systems are based on, or support, a graph data model called the Labeled Property Graph (LPG), where vertices and edges can have arbitrarily complex sets of labels and properties. We then develop LPG2vec, an encoder that transforms an arbitrary LPG dataset into a representation that can be directly used with a broad class of GNNs, including convolutional, attentional, message-passing, and even higher-order or spectral models. In our evaluation, we show that the rich information represented as LPG labels and properties is properly preserved by LPG2vec, and it increases the accuracy of predictions regardless of the targeted learning task or the used GNN model, by up to 34% compared to graphs with no LPG labels/properties. In general, LPG2vec enables combining predictive power of the most powerful GNNs with the full scope of information encoded in the LPG model, paving the way for neural graph databases, a class of systems where the vast complexity of maintained data will benefit from modern and future graph machine learning methods

A High-Performance Design, Implementation, Deployment, and Evaluation of The Slim Fly Network

Novel low-diameter network topologies such as Slim Fly (SF) offer significant cost and power advantages over the established Fat Tree, Clos, or Dragonfly. To spearhead the adoption of low-diameter networks, we design, implement, deploy, and evaluate the first real-world SF installation. We focus on deployment, management, and operational aspects of our test cluster with 200 servers and carefully analyze performance. We demonstrate techniques for simple cabling and cabling validation as well as a novel high-performance routing architecture for InfiniBand-based low-diameter topologies. Our real-world benchmarks show SF's strong performance for many modern workloads such as deep neural network training, graph analytics, or linear algebra kernels. SF outperforms non-blocking Fat Trees in scalability while offering comparable or better performance and lower cost for large network sizes. Our work can facilitate deploying SF while the associated (open-source) routing architecture is fully portable and applicable to accelerate any low-diameter interconnect

Antioxidant activities and phenolic contents of the methanol extracts of the stems of Acokanthera oppositifolia and Adenia gummifera

Abstract Background Acokanthera oppositifolia Lam (family: Apocynaceae) is a shrub or small tree with white latex, and the leaves of this plant are used in the form of a snuff to treat headaches and in infusions for abdominal pains and convulsions and septicaemia. Adenia gummifera Harv of the family Passifloraceae is a distinctive woody climber whose infusions are used as emetics and are said to help with some forms of depression. Lipid peroxidation has gained more importance today because of its involvement in pathogenesis of many diseases. Free radicals are the main agents in lipid peroxidation. Antioxidants thus play an important role of protecting the human body against damage by the free radicals. Plants containing phenolic compounds have been reported to possess strong antioxidant properties. Methods The antioxidant activities and phenolic contents of the methanol extracts of the stems of Acokanthera oppositifolia and Adenia gummifera were evaluated using in vitro standard procedures. Spectrophotometry was the basis for the determinations of total phenol, total flavonoids, flavonols, and proanthocyanidins. Tannins, quercetin and catechin equivalents were used for these parameters. The antioxidant activities of the stem extract of Acokanthera oppositifolia were determined by the 2,2'-azinobis-3- ethylbenzothiazoline-6-sulfonic acid (ABTS), 1,1-Diphenyl-2-picrylhydrazyl (DPPH), and ferrous reducing antioxidant property (FRAP) methods. Results The results from this study showed that the antioxidant activities of the stem extract of Acokanthera oppositifolia as determined by the 1,1-Diphenyl-2-picrylhydrazyl (DPPH), and ferrous reducing antioxidant property (FRAP) methods, were higher than that of Adenia gummifera. The levels of total phenols and flavonols for A. oppositifolia were also higher. On the other hand, the stem extract of Adenia gummifera had higher level of total flavonoids and proanthocyanidins than that of Acokanthera oppositifolia. The 2, 2'-azinobis-3- ethylbenzothiazoline-6-sulfonic acid (ABTS) activities of the 2 plant extracts were similar and comparable to that of BHT. Conclusion Thus, the present results indicate clearly that the extracts of Acokanthera oppositifolia and Adenia gummifera possess antioxidant properties and could serve as free radical inhibitors or scavengers, acting possibly as primary antioxidants. This study has to some extent validated the medicinal potential of the stems of Acokanthera oppositifolia and Adenia gummifera.</p

Assessment of the medicinal potentials of the methanol extracts of the leaves and stems of Buddleja saligna

<p>Abstract</p> <p>Background</p> <p><it>Buddleja saligna </it>Willd (Loganiaceae) is a small to medium-sized evergreen tree; trunk short, often gnarled and crooked; crown dense, rounded or domed-shaped; foliage greyish green. The wild olives are traditionally used to lower blood pressures in many parts of the world. In southern Africa, bark and leaf decoctions are used to treat colic, coughs, colds, sore eyes, urinary problems and as purgatives.</p> <p>Methods</p> <p>The antibacterial, antioxidant activities and phenolic contents of the methanol extracts of the leaves and stems of <it>Buddleja saligna </it>were evaluated using <it>in vitro </it>standard methods. Spectrophotometry was the basis for the determinations of total phenol, total flavonoids, flavonols, and proanthocyanidins. Tannins, quercetin and catechin equivalents were used for these parameters. The antioxidant activities of the leaves and stem extracts of <it>Buddleja saligna </it>were determined by ABTS, DPPH, and ferrous reducing antioxidant property (FRAP) methods. Laboratory isolates of 10 bacteria species which included five Gram-positive and five Gram-negative strains were used to assay for antibacterial activity of this plant.</p> <p>Results</p> <p>The antioxidant activities of the leaves as determined by the ABTS and DPPH were similar to that of the stem. The flavonoids and the flavonols contents of the leaves were higher than that of the stem but the total phenols, proanthocyanidins and FRAP activities were higher in the methanol extracts of the stem. The extracts did show activity against both Gram-positive and Gram-negative bacteria. For instance, while the methanol extract of the leaves showed good activities on all the organisms except <it>Serratia marcescens </it>and <it>Pseudomonas aeruginosa </it>at MICs of between 2.5 and 5.0 mg/ml, the extract of the stem only showed activities on <it>Bacillus cereus, Streptococcus pyrogens </it>and <it>Pseudomonas aeruginosa </it>at the same concentration.</p> <p>Conclusion</p> <p>The results from this study indicate that the leaves and stem extracts of <it>Buddleja saligna </it>possess antioxidant properties and could serve as free radical inhibitors or scavenger or, acting possibly as primary antioxidants. Although, the antibacterial properties of <it>Buddleja saligna </it>are not as effective as the standard drugs-Chloramphenicol and Streptomycin, they still possess some activity against bacterial strains used in this study. <it>Buddleja saligna </it>may therefore be a good candidate for functional foods as well as pharmaceutical plant-based products.</p

Obesity Trends and Body Mass Index Changes After Starting Antiretroviral Treatment: The Swiss HIV Cohort Study

The factors that contribute to increasing obesity rates in human immunodeficiency virus (HIV)-positive persons and to body mass index (BMI) increase that typically occurs after starting antiretroviral therapy (ART) are incompletely characterized

ProbGraph: High-Performance and High-Accuracy Graph Mining with Probabilistic Set Representations

Important graph mining problems such as Clustering are computationally demanding. To significantly accelerate these problems, we propose ProbGraph: a graph representation that enables simple and fast approximate parallel graph mining with strong theoretical guarantees on work, depth, and result accuracy. The key idea is to represent sets of vertices using probabilistic set representations such as Bloom filters. These representations are much faster to process than the original vertex sets thanks to vectorizability and small size. We use these representations as building blocks in important parallel graph mining algorithms such as Clique Counting or Clustering. When enhanced with ProbGraph, these algorithms significantly outperform tuned parallel exact baselines (up to nearly 50x on 32 cores) while ensuring accuracy of more than 90% for many input graph datasets. Our novel bounds and algorithms based on probabilistic set representations with desirable statistical properties are of separate interest for the data analytics community