8 research outputs found
A Search for Good Pseudo-random Number Generators : Survey and Empirical Studies
In today's world, several applications demand numbers which appear random but
are generated by a background algorithm; that is, pseudo-random numbers. Since
late century, researchers have been working on pseudo-random number
generators (PRNGs). Several PRNGs continue to develop, each one demanding to be
better than the previous ones. In this scenario, this paper targets to verify
the claim of so-called good generators and rank the existing generators based
on strong empirical tests in same platforms. To do this, the genre of PRNGs
developed so far has been explored and classified into three groups -- linear
congruential generator based, linear feedback shift register based and cellular
automata based. From each group, well-known generators have been chosen for
empirical testing. Two types of empirical testing has been done on each PRNG --
blind statistical tests with Diehard battery of tests, TestU01 library and NIST
statistical test-suite and graphical tests (lattice test and space-time diagram
test). Finally, the selected PRNGs are divided into groups and are
ranked according to their overall performance in all empirical tests
SPARTS: Simulator for Power Aware and Real-Time Systems
Real-time systems demand guaranteed and predictable run-time behaviour in order to ensure that no task has missed its deadline. Over the years we are witnessing an ever increasing demand for functionality enhancements in the embedded real-time systems. Along with the functionalities, the design itself grows more complex. Posed constraints, such as energy consumption, time, and space bounds, also require attention and proper handling. Additionally, efficient scheduling algorithms, as proven through analyses and simulations, often impose requirements that have significant run-time cost, specially in the context of multi-core systems. In order to further investigate the behaviour of such systems to quantify and compare these overheads involved, we have developed the SPARTS, a simulator of a generic embedded real- time device. The tasks in the simulator are described by externally visible parameters (e.g. minimum inter-arrival, sporadicity, WCET, BCET, etc.), rather than the code of the tasks. While our current implementation is primarily focused on our immediate needs in the area of power-aware scheduling, it is designed to be extensible to accommodate different task properties, scheduling algorithms and/or hardware models for the application in wide variety of simulations. The source code of the SPARTS is available for download at [1]
Parallel Implementation of Reinforcement Learning Q-Learning Technique for FPGA
Q-learning is an off-policy reinforcement learning technique, which has the main advantage of obtaining an optimal policy interacting with an unknown model environment. This paper proposes a parallel fixed-point Q-learning algorithm architecture implemented on field programmable gate arrays (FPGA) focusing on optimizing the system processing time. The convergence results are presented, and the processing time and occupied area were analyzed for different states and actions sizes scenarios and various fixed-point formats. The studies concerning the accuracy of the Q-learning technique response and resolution error associated with a decrease in the number of bits were also carried out for hardware implementation. The architecture implementation details were featured. The entire project was developed using the system generator platform (Xilinx), with a Virtex-6 xc6vcx240t-1ff1156 as the target FPGA
Computational Physics: An Introduction to Monte Carlo Simulations of Matrix Field Theory
This book is divided into two parts. In the first part we give an elementary
introduction to computational physics consisting of 21 simulations which
originated from a formal course of lectures and laboratory simulations
delivered since 2010 to physics students at Annaba University. The second part
is much more advanced and deals with the problem of how to set up working Monte
Carlo simulations of matrix field theories which involve finite dimensional
matrix regularizations of noncommutative and fuzzy field theories, fuzzy spaces
and matrix geometry. The study of matrix field theory in its own right has also
become very important to the proper understanding of all noncommutative, fuzzy
and matrix phenomena. The second part, which consists of 9 simulations, was
delivered informally to doctoral students who are working on various problems
in matrix field theory. Sample codes as well as sample key solutions are also
provided for convenience and completness. An appendix containing an executive
arabic summary of the first part is added at the end of the book.Comment: 350 pages, v2: slight change in titl
Review of Particle Physics
The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,143 new measurements from 709 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Among the 120 reviews are many that are new or heavily revised, including a new review on Machine Learning, and one on Spectroscopy of Light Meson Resonances.
The Review is divided into two volumes. Volume 1 includes the Summary Tables and 97 review articles. Volume 2 consists of the Particle Listings and contains also 23 reviews that address specific aspects of the data presented in the Listings.
The complete Review (both volumes) is published online on the website of the Particle Data Group (pdg.lbl.gov) and in a journal. Volume 1 is available in print as the PDG Book. A Particle Physics Booklet with the Summary Tables and essential tables, figures, and equations from selected review articles is available in print, as a web version optimized for use on phones, and as an Android app
Review of Particle Physics
The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,143
new measurements from 709 papers, we list, evaluate, and average measured properties of gauge bosons and the
recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical
particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search
limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs
Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology,
Particle Detectors, Colliders, Probability and Statistics. Among the 120 reviews are many that are new or heavily
revised, including a new review on Machine Learning, and one on Spectroscopy of Light Meson Resonances.
The Review is divided into two volumes. Volume 1 includes the Summary Tables and 97 review articles. Volume
2 consists of the Particle Listings and contains also 23 reviews that address specific aspects of the data presented
in the Listings.
The complete Review (both volumes) is published online on the website of the Particle Data Group (pdg.lbl.gov)
and in a journal. Volume 1 is available in print as the PDG Book. A Particle Physics Booklet with the Summary
Tables and essential tables, figures, and equations from selected review articles is available in print, as a web version
optimized for use on phones, and as an Android app.United States Department of Energy (DOE) DE-AC02-05CH11231government of Japan (Ministry of Education, Culture, Sports, Science and Technology)Istituto Nazionale di Fisica Nucleare (INFN)Physical Society of Japan (JPS)European Laboratory for Particle Physics (CERN)United States Department of Energy (DOE
Review of Particle Physics
The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,143 new measurements from 709 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Among the 120 reviews are many that are new or heavily revised, including a new review on Machine Learning, and one on Spectroscopy of Light Meson Resonances.
The Review is divided into two volumes. Volume 1 includes the Summary Tables and 97 review articles. Volume 2 consists of the Particle Listings and contains also 23 reviews that address specific aspects of the data presented in the Listings