Multi-GPU Graph Analytics

We present a single-node, multi-GPU programmable graph processing library that allows programmers to easily extend single-GPU graph algorithms to achieve scalable performance on large graphs with billions of edges. Directly using the single-GPU implementations, our design only requires programmers to specify a few algorithm-dependent concerns, hiding most multi-GPU related implementation details. We analyze the theoretical and practical limits to scalability in the context of varying graph primitives and datasets. We describe several optimizations, such as direction optimizing traversal, and a just-enough memory allocation scheme, for better performance and smaller memory consumption. Compared to previous work, we achieve best-of-class performance across operations and datasets, including excellent strong and weak scalability on most primitives as we increase the number of GPUs in the system.Comment: 12 pages. Final version submitted to IPDPS 201

Gunrock: GPU Graph Analytics

For large-scale graph analytics on the GPU, the irregularity of data access and control flow, and the complexity of programming GPUs, have presented two significant challenges to developing a programmable high-performance graph library. "Gunrock", our graph-processing system designed specifically for the GPU, uses a high-level, bulk-synchronous, data-centric abstraction focused on operations on a vertex or edge frontier. Gunrock achieves a balance between performance and expressiveness by coupling high performance GPU computing primitives and optimization strategies with a high-level programming model that allows programmers to quickly develop new graph primitives with small code size and minimal GPU programming knowledge. We characterize the performance of various optimization strategies and evaluate Gunrock's overall performance on different GPU architectures on a wide range of graph primitives that span from traversal-based algorithms and ranking algorithms, to triangle counting and bipartite-graph-based algorithms. The results show that on a single GPU, Gunrock has on average at least an order of magnitude speedup over Boost and PowerGraph, comparable performance to the fastest GPU hardwired primitives and CPU shared-memory graph libraries such as Ligra and Galois, and better performance than any other GPU high-level graph library.Comment: 52 pages, invited paper to ACM Transactions on Parallel Computing (TOPC), an extended version of PPoPP'16 paper "Gunrock: A High-Performance Graph Processing Library on the GPU

Chinese Medicines for Preventing and Treating Radiation-Induced Pulmonary Injury: Still a Long Way to Go

Thoracic radiotherapy is a mainstay of the treatment for lung, esophageal, and breast cancers. Radiation-induced pulmonary injury (RIPI) is a common side effect of thoracic radiotherapy, which may limit the radiotherapy dose and compromise the treatment results. However, the current strategies for RIPI are not satisfactory and may induce other side effects. Chinese medicines (CMs) have been used for more than a thousand years to treat a wide range of diseases, including lung disorders. In this review, we screened the literature from 2007 to 2017 in different online databases, including China National Knowledge Infrastructure (CNKI), Chongqing VIP, Wanfang, and PubMed; summarized the effectiveness of CMs in preventing and treating RIPI; explored the most frequently used drugs; and aimed to provide insights into potential CMs for RIPI. Altogether, CMs attenuated the risk of RIPI with an occurrence rate of 11.37% vs. 27.78% (P < 0.001) compared with the control groups. We also found that CMs (alone and combined with Western medical treatment) for treating RIPI exerted a higher efficacy rate than that of the control groups (78.33% vs. 28.09%, P < 0.001). In the screened literature, 38 CMs were used for the prevention and treatment of RIPI. The top five most frequently used CMs were Astragali Radix (with a frequency of 8.47%), Ophiopogonis Radix (with a frequency of 6.78%), Glycyrrhizae Radix et Rhizome (with a frequency of 5.08%), Paeoniae Radix Rubra (with a frequency of 5.08%), and Prunellae Spica (with a frequency of 5.08%). However, further high-quality investigations in CM source, pharmacological effects and underlying mechanisms, toxicological aspects, and ethical issues are warranted. Taken together, CMs might have a potential role in RIPI prevention and treatment and still have a long way to investigate

Performance Characterization of High-Level Programming Models for GPU Graph Analytics

We identify several factors that are critical to high-performance GPU graph analytics: efficient building block operators, synchronization and data movement, workload distribution and load balancing, and memory access patterns. We analyze the impact of these critical factors through three GPU graph analytic frameworks, Gunrock, MapGraph, and VertexAPI2. We also examine their effect on different workloads: four common graph primitives from multiple graph application domains, evaluated through real-world and synthetic graphs. We show that efficient building block operators enable more powerful operations for fast information propagation and result in fewer device kernel invocations, less data movement, and fewer global synchronizations, and thus are key focus areas for efficient large-scale graph analytics on the GPU

Preparation of water-soluble multi-walled carbon nanotubes by Ce(IV)-induced redox radical polymerization

Abstract Poly(acrylic acid), poly(N-isopropylacrylamide) and polyacrylamide functionalized MWNTs were prepared by Ce(IV)-induced redox radical polymerization. The reaction can be conducted in aqueous media at room temperature, and the polymer graft ratio increased with the increase of monomer feed ratio. MWNTs anchored with PAA on the surface are pH sensitive and exhibit a reversible assembly-deassembly response in aqueous solution, whereas those coated with PNIPAM are thermally sensitive. All the polymer-functionalized MWNTs are highly soluble in water to give robust stable black solutions. Such water-soluble MWNTs are promising for biological and biomedical applications