Supercomputers

Supercomputers news and articles

Content:
The shift towards high-bandwidth networks driven by AI workloads in data centers and HPC clusters has unintentionally aggravated network latency, adversely affecting the performance of communication-intensive HPC applications. As large-scale MPI applications often exhibit significant differences in their network latency tolerance, it is crucial to accurately determine the extent of network latency an application can withstand without significant performance degradation. Current approaches to ass...


Keywords: ai , network
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Effective code optimization in compilers plays a central role in computer and software engineering. While compilers can be made to automatically search the optimization space without the need for user interventions, this is not a standard practice since the search is slow and cumbersome. Here we present CodeZero, an artificial intelligence agent trained extensively on large data to produce effective optimization strategies instantly for each program in a single trial of the agent. To overcome th...


Keywords: artificial intelligence, optimization
Content:
BROMONT, QC,April 26, 2024 8212 IBM, the government of Canada and the government of Quebec today announced agreements to develop the assembly, testing and packaging ATP capabilities for semiconductor modules for telecommunications, high performa...


Keywords: generative, test, network, ai
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On Monday morning last month, tech executives, engineers and sales representatives from Amazon, Google, TikTok and other companies endured three hour traffic jam as their cars crawled toward mammoth conference at an event space in the desert, 50 mile...


Keywords: mathematic, artificial intelligence, scala, test
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Moving scientific computation from high-performance computing (HPC) and cloud computing (CC) environments to devices on the edge, i.e., physically near instruments of interest, has received tremendous interest in recent years. Such edge computing environments can operate on data in-situ, offering enticing benefits over data aggregation to HPC and CC facilities that include avoiding costs of transmission, increased data privacy, and real-time data analysis. Because of the inherent unreliability o...


Keywords: cloud computing, data analysis, edge
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Researchers have proposed local application of quantum trained Support Vector Machines SVMs to overcome the training set size limits of current quantum annealers. The team, including researchers from the University of Trento, Italy, the Jlich Super...


Keywords: supercomp, quant, scala, data analysis
Content:
With the rapid increase in machine learning workloads performed on HPC systems, it is beneficial to regularly perform machine learning specific benchmarks to monitor performance and identify issues. Furthermore, as part of the Edinburgh International Data Facility, EPCC currently hosts a wide range of machine learning accelerators including Nvidia GPUs, the Graphcore Bow Pod64 and Cerebras CS-2, which are managed via Kubernetes and Slurm. We extended the Reframe framework to support the Kubernet...


Keywords: machine learning, gpu, framework
Content:
We propose a notion of lift for quantum CSS codes, inspired by the geometrical construction of Freedman and Hastings. It is based on the existence of a canonical complex associated to any CSS code, that we introduce under the name of Tanner cone-complex, and over which we generate covering spaces. As a first application, we describe the classification of lifts of hypergraph product codes (HPC) and demonstrate the equivalence with the lifted product code (LPC) of Panteleev and Kalachev, including...


Keywords: metric, classification, quant, css
Content:
Efficient Reduce and AllReduce communication collectives are a critical cornerstone of high-performance computing (HPC) applications. We present the first systematic investigation of Reduce and AllReduce on the Cerebras Wafer-Scale Engine (WSE). This architecture has been shown to achieve unprecedented performance both for machine learning workloads and other computational problems like FFT. We introduce a performance model to estimate the execution time of algorithms on the WSE and validate our...


Keywords: machine learning, algorithms, computing

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