Готові списки джерел за темами / Mixed precision

Добірка наукової літератури з теми "Mixed precision"

Автор: Grafiati
Опубліковано: 7 липня 2024

Оформте джерело за APA, MLA, Chicago, Harvard та іншими стилями

Оберіть тип джерела:

Ознайомтеся зі списками актуальних статей, книг, дисертацій, тез та інших наукових джерел на тему "Mixed precision".

Біля кожної праці в переліку літератури доступна кнопка «Додати до бібліографії». Скористайтеся нею – і ми автоматично оформимо бібліографічне посилання на обрану працю в потрібному вам стилі цитування: APA, MLA, «Гарвард», «Чикаго», «Ванкувер» тощо.

Також ви можете завантажити повний текст наукової публікації у форматі «.pdf» та прочитати онлайн анотацію до роботи, якщо відповідні параметри наявні в метаданих.

Зміст

  1. Статті в журналах
  2. Дисертації
  3. Книги
  4. Частини книг
  5. Тези доповідей конференцій
  6. Звіти організацій

Статті в журналах з теми "Mixed precision":

1

Higham, Nicholas J., and Theo Mary. "Mixed precision algorithms in numerical linear algebra." Acta Numerica 31 (May 2022): 347–414. http://dx.doi.org/10.1017/s0962492922000022.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Today’s floating-point arithmetic landscape is broader than ever. While scientific computing has traditionally used single precision and double precision floating-point arithmetics, half precision is increasingly available in hardware and quadruple precision is supported in software. Lower precision arithmetic brings increased speed and reduced communication and energy costs, but it produces results of correspondingly low accuracy. Higher precisions are more expensive but can potentially provide great benefits, even if used sparingly. A variety of mixed precision algorithms have been developed that combine the superior performance of lower precisions with the better accuracy of higher precisions. Some of these algorithms aim to provide results of the same quality as algorithms running in a fixed precision but at a much lower cost; others use a little higher precision to improve the accuracy of an algorithm. This survey treats a broad range of mixed precision algorithms in numerical linear algebra, both direct and iterative, for problems including matrix multiplication, matrix factorization, linear systems, least squares, eigenvalue decomposition and singular value decomposition. We identify key algorithmic ideas, such as iterative refinement, adapting the precision to the data, and exploiting mixed precision block fused multiply–add operations. We also describe the possible performance benefits and explain what is known about the numerical stability of the algorithms. This survey should be useful to a wide community of researchers and practitioners who wish to develop or benefit from mixed precision numerical linear algebra algorithms.
2

Ralha, Rui. "Mixed Precision Bisection." Mathematics in Computer Science 12, no. 2 (March 13, 2018): 173–81. http://dx.doi.org/10.1007/s11786-018-0336-6.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Liu, Xingchao, Mao Ye, Dengyong Zhou, and Qiang Liu. "Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 10 (May 18, 2021): 8697–705. http://dx.doi.org/10.1609/aaai.v35i10.17054.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
We consider the post-training quantization problem, which discretizes the weights of pre-trained deep neural networks without re-training the model. We propose multipoint quantization, a quantization method that approximates a full-precision weight vector using a linear combination of multiple vectors of low-bit numbers; this is in contrast to typical quantization methods that approximate each weight using a single low precision number. Computationally, we construct the multipoint quantization with an efficient greedy selection procedure, and adaptively decides the number of low precision points on each quantized weight vector based on the error of its output. This allows us to achieve higher precision levels for important weights that greatly influence the outputs, yielding an ``effect of mixed precision'' but without physical mixed precision implementations (which requires specialized hardware accelerators). Empirically, our method can be implemented by common operands, bringing almost no memory and computation overhead. We show that our method outperforms a range of state-of-the-art methods on ImageNet classification and it can be generalized to more challenging tasks like PASCAL VOC object detection.
4

Van Zee, Field G., Devangi N. Parikh, and Robert A. Van De Geijn. "Supporting Mixed-domain Mixed-precision Matrix Multiplication within the BLIS Framework." ACM Transactions on Mathematical Software 47, no. 2 (April 2021): 1–26. http://dx.doi.org/10.1145/3402225.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
We approach the problem of implementing mixed-datatype support within the general matrix multiplication ( gemm ) operation of the BLAS-like Library Instantiation Software framework, whereby each matrix operand A , B , and C may be stored as single- or double-precision real or complex values. Another factor of complexity, whereby the matrix product and accumulation are allowed to take place in a precision different from the storage precisions of either A or B , is also discussed. We first break the problem into orthogonal dimensions, considering the mixing of domains separately from mixing precisions. Support for all combinations of matrix operands stored in either the real or complex domain is mapped out by enumerating the cases and describing an implementation approach for each. Supporting all combinations of storage and computation precisions is handled by typecasting the matrices at key stages of the computation—during packing and/or accumulation, as needed. Several optional optimizations are also documented. Performance results gathered on a 56-core Marvell ThunderX2 and a 52-core Intel Xeon Platinum demonstrate that high performance is mostly preserved, with modest slowdowns incurred from unavoidable typecast instructions. The mixed-datatype implementation confirms that combinatorial intractability is avoided, with the framework relying on only two assembly microkernels to implement 128 datatype combinations.
5

Kim, Han-Byul, Joo Hyung Lee, Sungjoo Yoo, and Hong-Seok Kim. "MetaMix: Meta-State Precision Searcher for Mixed-Precision Activation Quantization." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 12 (March 24, 2024): 13132–41. http://dx.doi.org/10.1609/aaai.v38i12.29212.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Mixed-precision quantization of efficient networks often suffer from activation instability encountered in the exploration of bit selections. To address this problem, we propose a novel method called MetaMix which consists of bit selection and weight training phases. The bit selection phase iterates two steps, (1) the mixed-precision-aware weight update, and (2) the bit-search training with the fixed mixed-precision-aware weights, both of which combined reduce activation instability in mixed-precision quantization and contribute to fast and high-quality bit selection. The weight training phase exploits the weights and step sizes trained in the bit selection phase and fine-tunes them thereby offering fast training. Our experiments with efficient and hard-to-quantize networks, i.e., MobileNet v2 and v3, and ResNet-18 on ImageNet show that our proposed method pushes the boundary of mixed-precision quantization, in terms of accuracy vs. operations, by outperforming both mixed- and single-precision SOTA methods.
6

Kelley, C. T. "Newton's Method in Mixed Precision." SIAM Review 64, no. 1 (February 2022): 191–211. http://dx.doi.org/10.1137/20m1342902.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Le Gallo, Manuel, Abu Sebastian, Roland Mathis, Matteo Manica, Heiner Giefers, Tomas Tuma, Costas Bekas, Alessandro Curioni, and Evangelos Eleftheriou. "Mixed-precision in-memory computing." Nature Electronics 1, no. 4 (April 2018): 246–53. http://dx.doi.org/10.1038/s41928-018-0054-8.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Ma, Yuexiao, Taisong Jin, Xiawu Zheng, Yan Wang, Huixia Li, Yongjian Wu, Guannan Jiang, Wei Zhang, and Rongrong Ji. "OMPQ: Orthogonal Mixed Precision Quantization." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 7 (June 26, 2023): 9029–37. http://dx.doi.org/10.1609/aaai.v37i7.26084.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
To bridge the ever-increasing gap between deep neural networks' complexity and hardware capability, network quantization has attracted more and more research attention. The latest trend of mixed precision quantization takes advantage of hardware's multiple bit-width arithmetic operations to unleash the full potential of network quantization. However, existing approaches rely heavily on an extremely time-consuming search process and various relaxations when seeking the optimal bit configuration. To address this issue, we propose to optimize a proxy metric of network orthogonality that can be efficiently solved with linear programming, which proves to be highly correlated with quantized model accuracy and bit-width. Our approach significantly reduces the search time and the required data amount by orders of magnitude, but without a compromise on quantization accuracy. Specifically, we achieve 72.08% Top-1 accuracy on ResNet-18 with 6.7Mb parameters, which does not require any searching iterations. Given the high efficiency and low data dependency of our algorithm, we use it for the post-training quantization, which achieves 71.27% Top-1 accuracy on MobileNetV2 with only 1.5Mb parameters.
9

Lee, Jong-Eun, Kyung-Bin Jang, and Seung-Ho Lim. "Implementation and Performance Analysis of Mixed Precision-based CNN Inference." Journal of Korean Institute of Information Technology 21, no. 12 (December 31, 2023): 77–85. http://dx.doi.org/10.14801/jkiit.2023.21.12.77.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Al-Marakeby, A. "PRECISION ON DEMAND: A NOVEL LOSSLES MIXED-PRECISION COMPUTATION TECHNIQUE." Journal of Al-Azhar University Engineering Sector 15, no. 57 (October 1, 2020): 1046–56. http://dx.doi.org/10.21608/auej.2020.120378.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Більше джерел
Також вас можуть зацікавити розширені добірки на тему "Mixed precision" для конкретних типів джерел:
Статті в журналах Дисертації

Дисертації з теми "Mixed precision":

1

Omland, Steffen [Verfasser]. "Mixed Precision Multilevel Monte Carlo Algorithms for Reconfigurable Computing Systems / Steffen Omland." München : Verlag Dr. Hut, 2016. http://d-nb.info/1113336447/34.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

McEntee, Peter John. "The integration and validation of precision management tools in mixed farming systems." Thesis, Curtin University, 2016. http://hdl.handle.net/20.500.11937/54060.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
In mixed farming systems up to 40% of farm area is in pasture, yet little is known about sub-paddock spatial variability/stability during a pasture phase. Precision agriculture technologies were used to incorporate pasture phase spatial variability into mixed farming precision management. Variations in paddock productivity over time were correlated between both crop and pasture phases, allowing site specific management to be adopted in both crop and pasture phases. However, the relationship was weaker in drought years.
3

Steffy, Daniel E. "Topics in exact precision mathematical programming." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/39639.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
The focus of this dissertation is the advancement of theory and computation related to exact precision mathematical programming. Optimization software based on floating-point arithmetic can return suboptimal or incorrect resulting because of round-off errors or the use of numerical tolerances. Exact or correct results are necessary for some applications. Implementing software entirely in rational arithmetic can be prohibitively slow. A viable alternative is the use of hybrid methods that use fast numerical computation to obtain approximate results that are then verified or corrected with safe or exact computation. We study fast methods for sparse exact rational linear algebra, which arises as a bottleneck when solving linear programming problems exactly. Output sensitive methods for exact linear algebra are studied. Finally, a new method for computing valid linear programming bounds is introduced and proven effective as a subroutine for solving mixed-integer linear programming problems exactly. Extensive computational results are presented for each topic.
4

Gerest, Matthieu. "Using Block Low-Rank compression in mixed precision for sparse direct linear solvers." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS447.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Pour résoudre des systèmes linéaires creux de grande taille, on peut vouloir utiliser des méthodes directes, numériquement robustes, mais coûteuses en termes d'utilisation de la mémoire et de temps de résolution. C'est le cas de la méthode multifrontale, notamment implémentée par le solveur MUMPS. L’une des fonctionnalités disponibles dans ce solveur est l’utilisation de la compression Block Low-Rank (BLR), qui améliore les performances. L'objectif de cette thèse est d'explorer plusieurs pistes d'amélioration de cette compression BLR, de façon à améliorer les performances de la méthode multifrontale. En particulier, nous proposons une variante de la compression BLR utilisant simultanément plusieurs formats de nombres à virgule flottante (précision mixte). Notre démarche, basée sur une analyse d'erreur, permet dans un premier temps de réduire la complexité d'une factorisation LU de matrice dense, sans pour autant impacter l'erreur commise de façon significative. Dans un second temps, nous adaptons ces algorithmes à la méthode multifrontale. Une première implémentation utilise notre compression BLR en précision mixte comme format de stockage, et permet ainsi de réduire la consommation mémoire de MUMPS. Une seconde implémentation permet de combiner ces gains en mémoire avec des gains en temps lors de la phase de résolution de systèmes triangulaires, grâce à des calculs effectués en précision faible. Cependant, nous remarquons que cette étape n'est pas aussi performante que prévu en BLR, dans le cas d'un système linéaire à plusieurs seconds membres. Pour y remédier, nous proposons de nouvelles variantes BLR de la résolution de systèmes triangulaires, dans laquelle la localité mémoire a été améliorée. Nous justifions l'intérêt de cette approche grâce à une analyse de volume de communication. Nous implémentons nos algorithmes dans un prototype simplifié, puis dans MUMPS, et nous obtenons des gains en temps dans les deux cas
In order to solve large sparse linear systems, one may want to use a direct method, numerically robust but rather costly, both in terms of memory consumption and computation time. The multifrontal method belong to this class algorithms, and one of its high-performance parallel implementation is the solver MUMPS. One of the functionalities of MUMPS is the use of Block Low-Rank (BLR) matrix compression, that improves its performance. In this thesis, we present several new techniques aiming at further improving the performance of dense and sparse direct solvers, on top of using a BLR compression. In particular, we propose a new variant of BLR compression in which several floating-point formats are used simultaneously (mixed precision). Our approach is based on an error analysis, and it first allows to reduce the estimated cost of a LU factorization of a dense matrix, without having a significant impact on the error. Second, we adapt these algorithms to the multifrontal method. A first implementation uses our mixed-precision BLR compression as a storage format only, thus allowing to reduce the memory footprint of MUMPS. A second implementation allows to combine these memory gains with time reductions in the triangular solution phase, by switching computations to low precision. However, we notice performance issues related to BLR for this phase, in case the system has many right-hand sides. Therefore, we propose new BLR variants of triangular solution that improve the data locality and reduce data movements, as highlighted by a communication volume analysis. We implement our algorithms within a simplified prototype and within solver MUMPS. In both cases, we obtain time gains
5

Wolfram, Heiko. "Model Building, Control Design and Practical Implementation of a High Precision, High Dynamical MEMS Acceleration Sensor." Universitätsbibliothek Chemnitz, 2005. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200501921.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
This paper presents the whole process of building up a high precision, high dynamical MEMS acceleration sensor. The first samples have achieved a resolution of better than 500 micro g and a bandwidth of more than 200 Hz. The sensor fabrication technology is shortly covered in the paper. A theoretical model is built from the physical principles of the complete sensor system, consisting of the MEMS sensor, the charge amplifier and the PWM driver for the sensor element. The mathematical modeling also covers problems during startup. A reduced order model of the entire system is used to design a robust control with the Mixed-Sensitivity H-infinity Approach. Since the system has an unstable pole, imposed by the electrostatic field and time delay, caused by A/D-D/A conversation delay and DSP computing time, limitations for the control design are given. The theoretical model might be inaccurate or lacks of completeness, because the parameters for the theoretical model building vary from sample to sample or might be not known. A new identification scheme for open or closed-loop operation is deployed to obtain directly from the samples the parameters of the mechanical system and the voltage dependent gains. The focus of this paper is the complete system development and identification process including practical tests in a DSP TI-TMS320C3000 environment.
6

Bustamante, Danilo. "High-Precision, Mixed-Signal Mismatch Measurement of Metal-Oxide-Metal Capacitors and a 13-GHz 5-bit 360-Degree Phase Shifter." BYU ScholarsArchive, 2020. https://scholarsarchive.byu.edu/etd/9240.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
A high-precision mixed-signal mismatch measurement technique for metal-oxide metal (MoM) capacitors as well as the design of a 13-GHz 5-bit 360-degree phase shifter are presented. This thesis presents a high-precision, mixed-signal mismatch measurement technique for metal-oxide–metal capacitors. The proposed technique incorporates a switched-capacitor op amp within the measurement circuit to significantly improve the measurement precision while relaxing the resolution requirement on the backend analog-to-digital converter (ADC). The proposed technique is also robust against multiple types of errors. A detailed analysis is presented to quantify the sensitivity improvement of the proposed technique over the conventional one. In addition, this thesis proposes a multiplexing technique to measure a large number of capacitors in a single chip and a new layout to improve matching. A prototype fabricated in 180 nm CMOS technology demonstrates the ability to sense capacitor mismatch standard deviation as low as 0.045% with excellent repeatability, all without the need of a high-resolution ADC. The 13-GHz 5-bit 360-degree phase shifter consists of 2 stages. The first stage utilizes a delay line for 4-bit 180-degree phase shift. A second stage provides 1-bit 180-degree phase shift. The phase shifter includes gain tuning so as to allow a gain variation of less than 1 dB. The design has been fabricated in 180 nm CMOS technology and measurement results show a complete 360◦ phase shift with an average step size of 10.7◦ at 13-GHz. After calibration the phase shifter presented an output gain S21 of 0.5 dB with a gain variation of less than 1 dB across all codes at 13-GHz. The remaining s-parameter testing showed a S22 and S11 below -11 dB and a S12 below -49 dB at 13 GHz.
7

Geifman, Nophar, Richard E. Kennedy, Lon S. Schneider, Iain Buchan, and Roberta Diaz Brinton. "Data-driven identification of endophenotypes of Alzheimer’s disease progression: implications for clinical trials and therapeutic interventions." BIOMED CENTRAL LTD, 2018. http://hdl.handle.net/10150/627086.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Background: Given the complex and progressive nature of Alzheimer's disease (AD), a precision medicine approach for diagnosis and treatment requires the identification of patient subgroups with biomedically distinct and actionable phenotype definitions. Methods: Longitudinal patient-level data for 1160 AD patients receiving placebo or no treatment with a follow-up of up to 18 months were extracted from an integrated clinical trials dataset. We used latent class mixed modelling (LCMM) to identify patient subgroups demonstrating distinct patterns of change over time in disease severity, as measured by the Alzheimer's Disease Assessment Scale-cognitive subscale score. The optimal number of subgroups (classes) was selected by the model which had the lowest Bayesian Information Criterion. Other patient-level variables were used to define these subgroups' distinguishing characteristics and to investigate the interactions between patient characteristics and patterns of disease progression. Results: The LCMM resulted in three distinct subgroups of patients, with 10.3% in Class 1, 76.5% in Class 2 and 13.2% in Class 3. While all classes demonstrated some degree of cognitive decline, each demonstrated a different pattern of change in cognitive scores, potentially reflecting different subtypes of AD patients. Class 1 represents rapid decliners with a steep decline in cognition over time, and who tended to be younger and better educated. Class 2 represents slow decliners, while Class 3 represents severely impaired slow decliners: patients with a similar rate of decline to Class 2 but with worse baseline cognitive scores. Class 2 demonstrated a significantly higher proportion of patients with a history of statins use; Class 3 showed lower levels of blood monocytes and serum calcium, and higher blood glucose levels. Conclusions: Our results, 'learned' from clinical data, indicate the existence of at least three subgroups of Alzheimer's patients, each demonstrating a different trajectory of disease progression. This hypothesis-generating approach has detected distinct AD subgroups that may prove to be discrete endophenotypes linked to specific aetiologies. These findings could enable stratification within a clinical trial or study context, which may help identify new targets for intervention and guide better care.
8

Di, Pace Brian S. "Site- and Location-Adjusted Approaches to Adaptive Allocation Clinical Trial Designs." VCU Scholars Compass, 2019. https://scholarscompass.vcu.edu/etd/5706.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Response-Adaptive (RA) designs are used to adaptively allocate patients in clinical trials. These methods have been generalized to include Covariate-Adjusted Response-Adaptive (CARA) designs, which adjust treatment assignments for a set of covariates while maintaining features of the RA designs. Challenges may arise in multi-center trials if differential treatment responses and/or effects among sites exist. We propose Site-Adjusted Response-Adaptive (SARA) approaches to account for inter-center variability in treatment response and/or effectiveness, including either a fixed site effect or both random site and treatment-by-site interaction effects to calculate conditional probabilities. These success probabilities are used to update assignment probabilities for allocating patients between treatment groups as subjects accrue. Both frequentist and Bayesian models are considered. Treatment differences could also be attributed to differences in social determinants of health (SDH) that often manifest, especially if unmeasured, as spatial heterogeneity amongst the patient population. In these cases, patient residential location can be used as a proxy for these difficult to measure SDH. We propose the Location-Adjusted Response-Adaptive (LARA) approach to account for location-based variability in both treatment response and/or effectiveness. A Bayesian low-rank kriging model will interpolate spatially-varying joint treatment random effects to calculate the conditional probabilities of success, utilizing patient outcomes, treatment assignments and residential information. We compare the proposed methods with several existing allocation strategies that ignore site for a variety of scenarios where treatment success probabilities vary.
9

Zulian, Marine. "Méthodes de sélection et de validation de modèles à effets mixtes pour la médecine génomique." Thesis, Institut polytechnique de Paris, 2020. http://www.theses.fr/2020IPPAX003.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
L'étude de phénomènes biologiques complexes tels que la physiopathologie humaine, la pharmacocinétique d'un médicament ou encore sa pharmacodynamie peut être enrichie par des approches de modélisation et de simulation. Les progrès technologiques de la génétique permettent la constitution de jeux de données issues de populations plus larges et plus hétérogènes. L'enjeu est alors de développer des outils intégrant les données génomiques et phénotypiques permettant d'expliquer la variabilité inter-individuelle. Dans cette thèse, nous développons des méthodes qui permettent de prendre en compte la complexité des données biologiques et la complexité des processus sous-jacents. Des étapes de curation des covariables génomiques nous permettent de restreindre le nombre de covariables potentielles ainsi que de limiter les corrélations entre covariables. Nous proposons un algorithme de sélection de covariables dans un modèle à effets mixtes dont la structure est contrainte par le processus physiologique étudié. En particulier, nous illustrons les méthodes développées sur deux applications issues de la médecine : des données réelles d'hypertension artérielle et des données simulées du métabolisme du tramadol (opioïde)
The study of complex biological phenomena such as human pathophysiology, pharmacokinetics of a drug or its pharmacodynamics can be enriched by modelling and simulation approaches. Technological advances in genetics allow the establishment of data sets from larger and more heterogeneous populations. The challenge is then to develop tools that integrate genomic and phenotypic data to explain inter-individual variability. In this thesis, we develop methods that take into account the complexity of biological data and the complexity of underlying processes. Curation steps of genomic covariates allow us to limit the number of potential covariates and limit correlations between covariates. We propose an algorithm for selecting covariates in a mixed effects model whose structure is constrained by the physiological process. In particular, we illustrate the developed methods on two medical applications: actual high blood pressure data and simulated tramadol (opioid) metabolism data
10

Cardoso, Adilson Silva. "Design and characterization of BiCMOS mixed-signal circuits and devices for extreme environment applications." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/53099.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
State-of-the-art SiGe BiCMOS technologies leverage the maturity of deep-submicron silicon CMOS processing with bandgap-engineered SiGe HBTs in a single platform that is suitable for a wide variety of high performance and highly-integrated applications (e.g., system-on-chip (SOC), system-in-package (SiP)). Due to their bandgap-engineered base, SiGe HBTs are also naturally suited for cryogenic electronics and have the potential to replace the costly de facto technologies of choice (e.g., Gallium-Arsenide (GaAs) and Indium-Phosphide (InP)) in many cryogenic applications such as radio astronomy. This work investigates the response of mixed-signal circuits (both RF and analog circuits) when operating in extreme environments, in particular, at cryogenic temperatures and in radiation-rich environments. The ultimate goal of this work is to attempt to fill the existing gap in knowledge on the cryogenic and radiation response (both single event transients (SETs) and total ionization dose (TID)) of specific RF and analog circuit blocks (i.e., RF switches and voltage references). The design approach for different RF switch topologies and voltage references circuits are presented. Standalone Field Effect Transistors (FET) and SiGe HBTs test structures were also characterized and the results are provided to aid in the analysis and understanding of the underlying mechanisms that impact the circuits' response. Radiation mitigation strategies to counterbalance the damaging effects are investigated. A comprehensive study on the impact of cryogenic temperatures on the RF linearity of SiGe HBTs fabricated in a new 4th-generation, 90 nm SiGe BiCMOS technology is also presented.
Більше джерел

Книги з теми "Mixed precision":

1

Li, Wei, Leilei Ji, Ramesh Agarwal, Weidong Shi, and Ling Zhou. Mixed-flow Pumps: Modeling, Simulation, and Measurements. ASME-Wiley, 2024. http://dx.doi.org/10.1115/1.862mfp.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Learn to improve and optimize the design and operation of mixed-flow pumps. Mixed-flow pumps have a huge range of applications in agriculture, hydroelectric power, and other industries that incorporate fluid transport. They are centrifugal pumps incorporating the characteristics of both axial and radial pumps to increase the flow rate and discharge pressure. Though essential in a variety of industries, they pose serious challenges to numerical simulation methods, challenges which are starting to be met by the application of computational fluid dynamics using high-performance computing. Mixed-flow Pumps introduces engineers and researchers to this subject and its important applications. Incorporating all major varieties of mixed-flow pumps used in industrial applications, it employs methods from advanced computational fluid dynamics and high-precision flow field experimentation to characterize and analyze these crucial technologies. Moving from the fundamentals of the technology to its most advanced applications, it’s an essential resource for engineers and industry practitioners looking to develop their understanding of fluid transport. Mixed-flow Pumps readers will also find: Mixed-flow Pumps is a useful reference for mixed-flow pump design by academic researchers, including graduate students, industry practitioners, and test engineers.
2

Champion, Erik Malcolm, ed. Virtual Heritage: A Concise Guide. Ubiquity Press, 2021. http://dx.doi.org/10.5334/bck.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
Virtual heritage has been explained as virtual reality applied to cultural heritage, but this definition only scratches the surface of the fascinating applications, tools and challenges of this fast-changing interdisciplinary field. This book provides an accessible but concise edited coverage of the main topics, tools and issues in virtual heritage. Leading international scholars have provided chapters to explain current issues in accuracy and precision; challenges in adopting advanced animation techniques; shows how archaeological learning can be developed in Minecraft; they propose mixed reality is conceptual rather than just technical; they explore how useful Linked Open Data can be for art history; explain how accessible photogrammetry can be but also ethical and practical issues for applying at scale; provide insight into how to provide interaction in museums involving the wider public; and describe issues in evaluating virtual heritage projects not often addressed even in scholarly papers. The book will be of particular interest to students and scholars in museum studies, digital archaeology, heritage studies, architectural history and modelling, virtual environments.
3

Arbustini, Eloisa, Valentina Favalli, Alessandro Di Toro, Alessandra Serio, and Jagat Narula. Classification of cardiomyopathies. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198784906.003.0348.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
Анотація:
For over 50 years, the definition and classification of cardiomyopathies have remained anchored in the concept of ventricular dysfunction and myocardial structural remodelling due to unknown cause. The concept of idiopathic was first challenged in 2006, when the American Heart Association classification subordinated the phenotype to the aetiology. Cardiomyopathies were classified as genetic, acquired, and mixed. In 2008, the European Society of Cardiology proposed a phenotype-driven classification that separated familial (genetic) from non-familial (non-genetic) forms of cardiomyopathy. Both classifications led the way to a precise phenotypic and aetiological description of the disease and moved away from the previously held notion of idiopathic disease. In 2013, the World Heart Federation introduced a descriptive and flexible nosology—the MOGE(S) classification—describing the morphofunctional (M) phenotype of cardiomyopathy, the involvement of additional organs (O), the familial/genetic (G) origin, and the precise description of the (a)etiology including genetic mutation, if applicable (E); reporting of functional status such as American College of Cardiology/American Heart Association stage and New York Heart Association classification (S) was left optional. MOGE(S) is a bridge between the past and the future. It allows description of comprehensive phenotypic data, all genetic and non-genetic causes of cardiomyopathy, and incorporates description of familial clustering in a genetic disease. MOGE(S) is the instrument of precision diagnosis for cardiomyopathies. The addition of the early and unaffected phenotypes to the (M) descriptor outlines the clinical profile of an early affected family member; the examples include non-dilated hypokinetic cardiomyopathy in dilated cardiomyopathy and septal thickness (13–14 mm) in hypertrophic cardiomyopathy classes.

Частини книг з теми "Mixed precision":

1

Kaminsky, W. "Pyrolysis of Mixed Plastics." In Precision Process Technology, 65–74. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-1759-3_6.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Stroup, Walter W., Marina Ptukhina, and Julie Garai. "Precision, Power, Sample Size, and Planning." In Generalized Linear Mixed Models, 599–631. 2nd ed. New York: Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9780429092060-24.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Fevre, Ralph. "Interdisciplinary and Mixed Methods Approaches to Study Workplace Bullying, Emotional Abuse and Harassment." In Precision Manufacturing, 1–28. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-5334-4_20-1.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

J. Molendijk, Maarten, Floran A. M. de Putter, and Henk Corporaal. "Low- and Mixed-Precision Inference Accelerators." In Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing, 63–88. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-19568-6_3.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Tsai, Yu-Hsiang Mike, Natalie Beams, and Hartwig Anzt. "Mixed Precision Algebraic Multigrid on GPUs." In Parallel Processing and Applied Mathematics, 113–25. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-30442-2_9.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Fuengfusin, Ninnart, and Hakaru Tamukoh. "Mixed Precision Weight Networks: Training Neural Networks with Varied Precision Weights." In Neural Information Processing, 614–23. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04179-3_54.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Martel, Matthieu. "Floating-Point Format Inference in Mixed-Precision." In Lecture Notes in Computer Science, 230–46. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57288-8_16.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Heimlich, A., A. C. A. Alvim, F. C. Silva, and A. S. Martinez. "GPU Based Mixed Precision PWR Depletion Calculation." In Integral Methods in Science and Engineering, Volume 2, 127–36. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59387-6_13.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Georgescu, Serban, and Hiroshi Okuda. "Automatically Tuned Mixed-Precision Conjugate Gradient Solver." In Software Automatic Tuning, 103–19. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-6935-4_7.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Wang, Mingkai, Taisong Jin, Miaohui Zhang, and Zhengtao Yu. "CSMPQ: Class Separability Based Mixed-Precision Quantization." In Lecture Notes in Computer Science, 544–55. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-4755-3_47.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.

Тези доповідей конференцій з теми "Mixed precision":

1

Santos, Fernando Fernandes dos, Marcelo Brandalero, Pedro Martins Basso, Michael Hubner, Luigi Carro, and Paolo Rech. "Reduced-Precision DWC for Mixed-Precision GPUs." In 2020 IEEE 26th International Symposium on On-Line Testing and Robust System Design (IOLTS). IEEE, 2020. http://dx.doi.org/10.1109/iolts50870.2020.9159748.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Geng, Xue, Jie Lin, and Shaohua Li. "Cascaded Mixed-Precision Networks." In 2020 IEEE International Conference on Image Processing (ICIP). IEEE, 2020. http://dx.doi.org/10.1109/icip40778.2020.9190760.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Loe, Jennifer, and Sivasankaran Rajamanickam. "Mixed Precision in Trilinos." In Proposed for presentation at the Trilinos User Group Meeting held November 30-December 2, 2021 in ,. US DOE, 2021. http://dx.doi.org/10.2172/1900352.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Damouche, Nasrine, and Matthieu Martel. "Mixed Precision Tuning with Salsa." In International Conference on Pervasive and Embedded Computing. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006915500470056.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Damouche, Nasrine, and Matthieu Martel. "Mixed Precision Tuning with Salsa." In International Conference on Pervasive and Embedded Computing. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0006915501850194.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Loe, Jennifer, Christian Glusa, Ichitaro Yamazaki, Erik Boman, and Sivasankaran Rajamanickam. "Mixed Precision Strategies for GMRES." In Proposed for presentation at the SIAM Parallel Processing 2022 held February 23-26, 2022 in Virtual,. US DOE, 2022. http://dx.doi.org/10.2172/2001827.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Loe, Jennifer, Christian Glusa, Ichitaro Yamazaki, Erik Boman, and Sivasankaran Rajamanickam. "Mixed-Precision GMRES in Trilinos." In Proposed for presentation at the Sandia Postdoctoral Technical Showcase held December 9-10, 2020 in Albuquerque, NM. US DOE, 2020. http://dx.doi.org/10.2172/1833786.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Bulat, Adrian, and Georgios Tzimiropoulos. "Bit-Mixer: Mixed-precision networks with runtime bit-width selection." In 2021 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2021. http://dx.doi.org/10.1109/iccv48922.2021.00514.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Fang, Bo, Siva Kumar Sastry Hari, Timothy Tsai, Xinyi Li, Ganesh Gopalakrishnan, Ignacio Laguna, Kevin Barker, and Ang Li. "Towards Precision-Aware Fault Tolerance Approaches for Mixed-Precision Applications." In 2022 IEEE/ACM 12th Workshop on Fault Tolerance for HPC at eXtreme Scale (FTXS). IEEE, 2022. http://dx.doi.org/10.1109/ftxs56515.2022.00010.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Darulova, Eva, Einar Horn, and Saksham Sharma. "Sound Mixed-Precision Optimization with Rewriting." In 2018 ACM/IEEE 9th International Conference on Cyber-Physical Systems (ICCPS). IEEE, 2018. http://dx.doi.org/10.1109/iccps.2018.00028.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.

Звіти організацій з теми "Mixed precision":

1

Higham, N., and S. Pranesh. Mixed Precision xsdk Project Final Report. Office of Scientific and Technical Information (OSTI), April 2021. http://dx.doi.org/10.2172/1777343.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
2

Carson, E. Final Report: Mixed Precision Numerical Linear Algebra. Office of Scientific and Technical Information (OSTI), June 2021. http://dx.doi.org/10.2172/1798446.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
3

Abdelfattah, A., H. Anzt, A. Ayala, E. Boman, E. Carson, S. Cayrols, T. Cojean, et al. Advances in Mixed Precision Algorithms: 2021 Edition. Office of Scientific and Technical Information (OSTI), August 2021. http://dx.doi.org/10.2172/1814677.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
4

Abdelfattah, Ahmad, Hartwig Anzt, Alan Ayala, Erik Boman, Erin Carson, Sebastien Cayrols, Terry Cojean, et al. Advances in Mixed Precision Algorithms: 2021 Edition. Office of Scientific and Technical Information (OSTI), August 2021. http://dx.doi.org/10.2172/1814447.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
5

Carson, E. Final Report: Mixed Precision Numerical Linear Algebra. Office of Scientific and Technical Information (OSTI), June 2022. http://dx.doi.org/10.2172/1872699.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
6

Carson, E. Final Report: Mixed Precision Numerical Linear Algebra. Office of Scientific and Technical Information (OSTI), October 2023. http://dx.doi.org/10.2172/2204467.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
7

Carson, E. Final Report: Mixed Precision Numerical Linear Algebra. Office of Scientific and Technical Information (OSTI), December 2023. http://dx.doi.org/10.2172/2280470.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
8

Anzt, H., E. Boman, M. Gates, S. Kruger, X. Li, J. Loe, D. Osei-Kuffuor, S. Tomov, Y. Tsai, and U. Yang. Towards Use of Mixed Precision in ECP Math Libraries. Office of Scientific and Technical Information (OSTI), November 2020. http://dx.doi.org/10.2172/1762902.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
9

Antz, Hartwig, Erik Boman, Mark Gates, Scott Kruger, Sherry Li, Jennifer Loe, Daniel Osei-Kuffuor, Stan Tomov, Yaohung Tsai, and Ulrike Meier Yang. Towards Use of Mixed Precision in ECP Math Libraries. Office of Scientific and Technical Information (OSTI), December 2020. http://dx.doi.org/10.2172/1735694.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.
10

Higham, N. Mixed Precision xsdk Project: Final Report for Subcontract B650966. Office of Scientific and Technical Information (OSTI), October 2023. http://dx.doi.org/10.2172/2204465.

Повний текст джерела
Стилі APA, Harvard, Vancouver, ISO та ін.

До бібліографії