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Harnessing the computing continuum for programming our world
This chapter outlines a vision for how best to harness the computing continuum of
interconnected sensors, actuators, instruments, and computing systems, from small numbers …
interconnected sensors, actuators, instruments, and computing systems, from small numbers …
A survey on evaluating and optimizing performance of Intel Xeon Phi
Summary Intel's Xeon Phi combines the parallel processing power of a many‐core
accelerator with the programming ease of CPUs. In this paper, we present a survey of works …
accelerator with the programming ease of CPUs. In this paper, we present a survey of works …
HeAT–a distributed and GPU-accelerated tensor framework for data analytics
To cope with the rapid growth in available data, the efficiency of data analysis and machine
learning libraries has recently received increased attention. Although great advancements …
learning libraries has recently received increased attention. Although great advancements …
HySec-Flow: privacy-preserving genomic computing with SGX-based big-data analytics framework
Trusted execution environments (TEE) such as In-tel's Software Guard Extension (SGX)
have been widely studied to boost security and privacy protection for the computation of …
have been widely studied to boost security and privacy protection for the computation of …
Dlobd: A comprehensive study of deep learning over big data stacks on hpc clusters
Deep Learning over Big Data (DLoBD) is an emerging paradigm to mine value from the
massive amount of gathered data. Many Deep Learning frameworks, like Caffe, TensorFlow …
massive amount of gathered data. Many Deep Learning frameworks, like Caffe, TensorFlow …
Effect of distributed directories in mesh interconnects
Recent manycore processors are kept coherent using scalable distributed directories. A
paramount example is the Xeon Phi Knights Landing. It features 38 tiles packed in a single …
paramount example is the Xeon Phi Knights Landing. It features 38 tiles packed in a single …
Exploring HPC and big data convergence: A graph processing study on Intel Knights Landing
The question" Can big data and HPC infrastructure converge?" has important implications
for many operators and clients of modern computing. However, answering it is challenging …
for many operators and clients of modern computing. However, answering it is challenging …
Harpgbdt: Optimizing gradient boosting decision tree for parallel efficiency
Gradient Boosting Decision Tree (GBDT) is a widely used machine learning algorithm,
whose training involves both irregular computation and random memory access and is …
whose training involves both irregular computation and random memory access and is …
Optimizing coherence traffic in manycore processors using closed-form caching/home agent map**s
Manycore processors feature a high number of general-purpose cores designed to work in a
multithreaded fashion. Recent manycore processors are kept coherent using scalable …
multithreaded fashion. Recent manycore processors are kept coherent using scalable …
Parallelization of network motif discovery using star contraction
ER Ateskan, K Erciyes, ME Dalkilic - Parallel Computing, 2021 - Elsevier
Network motifs are widely used to uncover structural design principles of complex networks.
Current sequential network motif discovery algorithms become inefficient as motif size …
Current sequential network motif discovery algorithms become inefficient as motif size …