Search Results - "Computing methodologies Distributed computing methodologies Distributed programming languages"

Skywalker: Efficient Alias-Method-Based Graph Sampling and Random Walk on GPUs by Wang, Pengyu, Li, Chao, Wang, Jing, Wang, Taolei, Zhang, Lu, Leng, Jingwen, Chen, Quan, Guo, Minyi

“…Graph sampling and random walk operations, capturing the structural properties of graphs, are playing an important role today as we cannot directly adopt…”
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MAD-Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems by Hsia, Samuel, Golden, Alicia, Acun, Bilge, Ardalani, Newsha, DeVito, Zachary, Wei, Gu-Yeon, Brooks, David, Wu, Carole-Jean

“…Training and deploying large-scale machine learning models is time-consuming, requires significant distributed computing infrastructures, and incurs high…”
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AdaGL: Adaptive Learning for Agile Distributed Training of Gigantic GNNs by Zhang, Ruisi, Javaheripi, Mojan, Ghodsi, Zahra, Bleiweiss, Amit, Koushanfar, Farinaz

“…Distributed GNN training on contemporary massive and densely connected graphs requires information aggregation from all neighboring nodes, which leads to an…”
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Gluon-Async: A Bulk-Asynchronous System for Distributed and Heterogeneous Graph Analytics by Dathathri, Roshan, Gill, Gurbinder, Hoang, Loc, Jatala, Vishwesh, Pingali, Keshav, Nandivada, V. Krishna, Dang, Hoang-Vu, Snir, Marc

“…Distributed graph analytics systems for CPUs, like D-Galois and Gemini, and for GPUs, like D-IrGL and Lux, use a bulk-synchronous parallel (BSP) programming…”
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Auto-parallelizing stateful distributed streaming applications by Schneider, Scott, Hirzel, Martin, Gedik, Bugra, Wu, Kun-Lung

“…Streaming applications transform possibly infinite streams of data and often have both high throughput and low latency requirements. They are comprised of…”
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Legate NumPy: Accelerated and Distributed Array Computing by Bauer, Michael, Garland, Michael

“…NumPy is a popular Python library used for performing array-based numerical computations. The canonical implementation of NumPy used by most programmers runs…”
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Risk and Mitigation of Nondeterminism in Distributed Cyber-Physical Systems by Bateni, Soroush, Lohstroh, Marten, Wong, Hou Seng, Kim, Hokeun, Lin, Shaokai, Menard, Christian, Lee, Edward A.

“…Asynchronous frameworks for distributed embedded systems, like ROS and MQTT, are increasingly used in safety-critical applications such as autonomous driving,…”
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Scalable and Consistent Graph Neural Networks for Distributed Mesh-based Data-driven Modeling by Barwey, Shivam, Balin, Riccardo, Lusch, Bethany, Patel, Saumil, Balakrishnan, Ramesh, Pal, Pinaki, Maulik, Romit, Vishwanath, Venkatram

“…This work develops a distributed graph neural network (GNN) methodology for mesh-based modeling applications using a consistent neural message passing layer…”
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Optimizing Distributed ML Communication with Fused Computation-Collective Operations by Punniyamurthy, Kishore, Hamidouche, Khaled, Beckmann, Bradford M.

“…Machine learning models are distributed across multiple nodes using numerous parallelism strategies. The resulting collective communication is often on the…”
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Stratified sampling for even workload partitioning by Paudel, Jeeva, Amaral, Jose Nelson

“…This work presents a novel algorithm, Workload Partitioning and Scheduling (WPS), for evenly partitioning the computational workload of large…”
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Unifying Artifacts and Activities in a Visual Tool for Distributed Software Development Teams by Froehlich, Jon, Dourish, Paul

“…In large projects, software developers struggle with two sources of complexity the complexity of the code itself, and the complexity of of the process of…”
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Legate Sparse: Distributed Sparse Computing in Python by Yadav, Rohan, Lee, Wonchan, Elibol, Melih, Patti, Taylor Lee, Papadakis, Manolis, Garland, Michael, Aiken, Alex, Kjolstad, Fredrik, Bauer, Michael

“…The sparse module of the popular SciPy Python library is widely used across applications in scientific computing, data analysis and machine learning. The…”
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Accelerating Communications in Federated Applications with Transparent Object Proxies by Pauloski, J. Gregory, Hayot-Sasson, Valerie, Ward, Logan, Hudson, Nathaniel, Sabino, Charlie, Baughman, Matt, Chard, Kyle, Foster, Ian

“…Advances in networks, accelerators, and cloud services encourage programmers to reconsider where to compute-such as when fast networks make it cost-effective…”
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CUDASTF: Bridging the Gap Between CUDA and Task Parallelism by Augonnet, Cedric, Alexandrescu, Andrei, Sidelnik, Albert, Garland, Michael

“…Organizing computation as asynchronous tasks with data-driven dependencies is a simple and efficient model for single- and multi-GPU programs. Sequential Task…”
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Managing Workflow Malleability in Urgent Computing for Earthquake Alerts by Ejarque, Jorge, Monterrubio-Velasco, Marisol, Bhihe, Cedric, Pienkowska, Marta, De La Puente, Josep, Badia, Rosa M.

“…When large earthquakes happen, first responders need fast and accurate information regarding their impact. UCIS4EQ is an urgent computing platform that…”
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Parallelized Multi-Agent Bayesian Optimization in Lava by Snyder, Shay, Gobin, Derek, Clerico, Victoria, Risbud, Sumedh R., Parsa, Maryam

“…In parallel with the continuously increasing parameter space dimensionality, search and optimization algorithms should support distributed parameter…”
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Multi-layer faults in the architectures of mobile, context-aware adaptive applications: a position paper by Sama, Michele, Rosenblum, David S, Wang, Zhimin, Elbaum, Sebastian

“…Five cellphones are sold every second, and there are four times more cellphones than computers, meaning there are some billions of mobile handheld devices in…”
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Asynchronous Distributed-Memory Parallel Algorithms for Influence Maximization by Singhal, Shubhendra Pal, Hati, Souvadra, Young, Jeffrey, Sarkar, Vivek, Hayashi, Akihiro, Vuduc, Richard

“…Influence maximization (IM) is the problem of finding the k most influential nodes in a graph. We propose distributed-memory parallel algorithms for the two…”
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Enabling Low-Overhead HT-HPC Workflows at Extreme Scale using GNU Parallel by Maheshwari, Ketan, Arndt, William, Karimi, Ahmad Maroof, Yin, Junqi, Suter, Frederic, Johnson, Seth, Da Silva, Rafael Ferreira

“…GNU Parallel is a versatile and powerful tool for process parallelization widely used in scientific computing. This paper demonstrates its effective…”
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Parsl+CWL: Towards Combining the Python and CWL Ecosystems by Karle, Nishchay, Clifford, Ben, Babuji, Yadu, Chard, Ryan, Katz, Daniel S., Chard, Kyle

“…The Common Workflow Language (CWL) is a widely adopted language for defining and sharing computational workflows. It is designed to be independent of the…”
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