335 research outputs found
De Eo Qvod Ivstvm Est Circa Festvm S. Archangeli Michaelis : Programma Sollemni Die Anniversario S. Michaelis A. R. S. MDCCLXII In Academia Ivlia Carolina P. P
No full textHelmstedt, Universität, Universitätsprogramm, 1762[Academiae Ivliae Carolinae Prorector D. Iohannes Iacobvs Hoefler ...]Teilw. in griech. Schr.Fingerprint nach Ex. der HAB Wolfenbüttel und der ULB Sachsen-AnhaltVorlageform des Erscheinungsvermerks: HelmstadI Litteris Vidvae B. Schnorrii Acad. Typogr. - Erscheinungsjahr nach der Datierung im Titel bestimm
Układ do zabezpieczenia napędu dźwignicowego opis patentowy nr 128466 /
No full textTyt. z ekranu tyt.Zgłoszono 17 października 1979 r.Zgłoszenie ogłoszono 24 kwietnia 1981 r.Opublikowano 30 listopada 1985 r.Pozostali twórcy wynalazku: Jerzy Cholewka, Zbigniew Kulski, Norbert Hoefler, Janusz Grzegorski, Wacław Paściak.Nr zgłoszenia P. 219046.Dostępny także w wersji drukowanej.Tryb dostępu: Internet
Indirection Stream Semantic Register Architecture for Efficient Sparse-Dense Linear Algebra
No full textSparse-dense linear algebra is crucial in many domains, but challenging to handle efficiently on CPUs, GPUs, and accelerators alike; multiplications with sparse formats like CSR and CSF require indirect memory lookups. In this work, we enhance a memory-streaming RISC-V ISA extension to accelerate sparse-dense products through streaming indirection. We present efficient dot, matrix-vector, and matrix-matrix product kernels using our hardware, enabling single-core FPU utilizations of up to 80% and speedups of up to 7.2x over an optimized baseline without extensions. A matrix-vector implementation on a multicore cluster is up to 5.8x faster and 2.7x more energy-efficient with our kernels than an optimized baseline. We propose further uses for our indirection hardware, such as scatter-gather operations and codebook decoding, and compare our work to state-of-the-art CPU, GPU, and accelerator approaches, measuring a 2.8x higher peak FP64 utilization in CSR matrix-vector multiplication than a GTX 1080 Ti GPU running a cuSPARSE kernel
Managing death
No full textDrawing on provocative case studies, personal interviews, and detailed research, James Hoefler examines the medical, legal, ethical, and clinical aspects of right-to-die issues. Beginning with the legal struggle of a woman whose son existed in a persistent vegetative state (PVS) for seventeen years, the author moves into a broader look at consensus among professional organizations, from the AMA to the President's Commission to the National Center for State Courts; beliefs of mainstream religious groups; public opinion; issues surrounding end-stage Alzheimer's and other organic brain disorders that can slowly lead to PVS; and the role of artificial nutrition and hydration in these casesHoefler concludes with recommendations on how to improve the quality of right-to-die decisionmaking. An absorbing read with a minimum of technical jargon, this book is a valuable guide to care givers, public policy students, medical ethicists, family members, and anyone facing questions about an individual's right to di
Mitigating Network Noise on Dragonfly Networks through Application-Aware Routing (code, data and scripts to reproduce paper results)
No full text<p>This repository contains the data, code, and scripts required to reproduce the results of the paper "Mitigating Network Noise on Dragonfly Networks through Application-Aware Routing" by Daniele De Sensi, Salvatore Di Girolamo and Torsten Hoefler, presented at the 2019 International Conference for High Performance Computing, Networking, Storage, and Analysis. </p>
<p>This repository does not contains the code of the library used to automatically tune the routing algorithm, which can be found at http://doi.org/10.5281/zenodo.3372785</p>
Scaling betweenness centrality using communication-efficient sparse matrix multiplication
No full textBetweenness centrality (BC) is a crucial graph problem that measures the significance of a vertex by the number of shortest paths
leading through it. We propose Maximal Frontier Betweenness Centrality (MFBC): a succinct BC algorithm based on novel sparse matrix multiplication routines that performs a factor of p 1/3 less communication on p processors than the best known alternatives, for
graphs withn vertices and average degree k = n/p 2/3. We formulate, implement, and prove the correctness of MFBC for weighted graphs by leveraging monoids instead of semirings, which enables a surprisingly succinct formulation. MFBC scales well for both extremely sparse and relatively dense graphs. It automatically searches a space of distributed data decompositions and sparse matrix multiplication algorithms for the most advantageous configuration. The MFBC implementation outperforms the well-known CombBLAS library by up to 8x and shows more robust performance. Our design methodology is readily extensible to other graph problems
Sposób sterowania napędu dźwignicowego z przemiennikiem częstotliwości oraz układ sterowania napędu dźwignicowego z przemiennikiem częstotliwości opis patentowy nr 127625 /
No full textZgłoszono 30 listopada 1979 r.Zgłoszenie ogłoszono 5 czerwca 1981 r.Opublikowano 30 listopada 1985 r.Nr zgłosz. P 220071.Tyt. z ekranu tyt.Pozostali współtwórcy wynalazku: Henryk Zygmunt, Jerzy Cholewka, Zbigniew Kulski, Norbert Hoefler, Marian Rohde, Janusz Grzegorski.Dostępny także w wersji drukowanej.Tryb dostępu: Internet
Mitigating Network Noise on Dragonfly Networks through Application-Aware Routing (library code only)
No full text<p>This repository contains the code of the library to automatically tune the adaptive routing algorithm, used in the paper "Mitigating Network Noise on Dragonfly Networks through Application-Aware Routing" by Daniele De Sensi, Salvatore Di Girolamo and Torsten Hoefler, presented at the 2019 International Conference for High Performance Computing, Networking, Storage, and Analysis.</p>
<p>You can find the updated version of the library at: <a href="https://github.com/DanieleDeSensi/awr">https://github.com/DanieleDeSensi/awr</a></p>
<p>Note that this repository only contains the code of the library. If you want to fully reproduce the results of the paper, you can find additional code, data and scripts in the following repository: http://doi.org/10.5281/zenodo.3372789<br>
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Mitigating Network Noise on Dragonfly Networks through Application-Aware Routing (code, data and scripts)
No full textThis repository contains source code, data and scripts used to generate the data shown in the paper "Mitigating Network Noise on Dragonfly Networks through Application-Aware Routing", by Daniele De Sensi, Salvatore Di Girolamo and Torsten Hoefler, presented at the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 2019).
An updated version of this repository can be found at https://bitbucket.org/DanieleDeSensi/sc19/src/master/
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