68 research outputs found
Petri Nets and Other Models of Concurrency
This paper retraces, collects, and summarises contributions of the authors --- in collaboration with others --- on the theme of Petri nets and their categorical relationships to other models of concurrency
An accurate prefetching policy for object oriented systems
PhD ThesisIn the latest high-performance computers, there is a growing requirement for
accurate prefetching(AP) methodologies for advanced object management schemes
in virtual memory and migration systems. The major issue for achieving this goal is that
of finding a simple way of accurately predicting the objects that will be referenced in
the near future and to group them so as to allow them to be fetched same time. The
basic notion of AP involves building a relationship for logically grouping related
objects and prefetching them, rather than using their physical grouping and it relies on
demand fetching such as is done in existing restructuring or grouping schemes. By this,
AP tries to overcome some of the shortcomings posed by physical grouping methods.
Prefetching also makes use of the properties of object oriented languages to
build inter and intra object relationships as a means of logical grouping. This thesis
describes how this relationship can be established at compile time and how it can be
used for accurate object prefetching in virtual memory systems. In addition, AP
performs control flow and data dependency analysis to reinforce the relationships and
to find the dependencies of a program. The user program is decomposed into
prefetching blocks which contain all the information needed for block prefetching such
as long branches and function calls at major branch points.
The proposed prefetching scheme is implemented by extending a C++
compiler and evaluated on a virtual memory simulator. The results show a significant
reduction both in the number of page fault and memory pollution. In particular, AP
can suppress many page faults that occur during transition phases which are
unmanageable by other ways of fetching. AP can be applied to a local and distributed
virtual memory system so as to reduce the fault rate by fetching groups of objects at the
same time and consequently lessening operating system overheads.British Counci
Compiling Data Dependent Control Flow on SIMD GPUs
Current Graphic Processing Units (GPUs) (circa. 2003/2004) have programmable vertex and fragment units. Often these units are implemented as SIMD processors employing parallel pipelines. Data dependent conditional execution on SIMD architectures implemented using processor idling is inefficient. I propose a multi-pass approach based on conditional streams which allows dynamic load balancing of the fragment units of the GPU and better theoretical performance on programs using data dependent conditionals and loops. The proposed system can be used to turn the fragment unit of a SIMD GPU into a stream processor with data dependent control flow
Elements of Petri nets and processes
We present a formalism for Petri nets based on polynomial-style finite-set
configurations and etale maps. The formalism supports both a geometric
semantics in the style of Goltz and Reisig (processes are etale maps from
graphs) and an algebraic semantics in terms of free coloured props: the Segal
space of P-processes is shown to be the free coloured prop-in-groupoids on P.
There is also an unfolding semantics \`a la Winskel, which bypasses the
classical symmetry problems. Since everything is encoded with explicit sets,
Petri nets and their processes have elements. In particular, individual-token
semantics is native, and the benefits of pre-nets in this respect can be
obtained without the need of numberings. (Collective-token semantics emerges
from rather drastic quotient constructions \`a la Best--Devillers, involving
taking of the groupoids of states.)Comment: 44 pages. The math is intended to be in reasonably final form, but
the paper may well contain some misconceptions regarding the place of this
material in the theory of Petri nets. All feedback and help will be greatly
appreciated. v2: fixed a mistake in Section
Computing Competencies for Undergraduate Data Science Curricula: ACM Data Science Task Force
At the August 2017 ACM Education Council meeting, a task force was formed to explore a process to add to the broad, interdisciplinary conversation on data science, with an articulation of the role of computing discipline-specific contributions to this emerging field. Specifically, the task force would seek to define what the computing/computational contributions are to this new field, and provide guidance on computing-specific competencies in data science for departments offering such programs of study at the undergraduate level.
There are many stakeholders in the discussion of data science – these include colleges and universities that (hope to) offer data science programs, employers who hope to hire a workforce with knowledge and experience in data science, as well as individuals and professional societies representing the fields of computing, statistics, machine learning, computational biology, computational social sciences, digital humanities, and others. There is a shared desire to form a broad interdisciplinary definition of data science and to develop curriculum guidance for degree programs in data science.
This volume builds upon the important work of other groups who have published guidelines for data science education. There is a need to acknowledge the definition and description of the individual contributions to this interdisciplinary field. For instance, those interested in the business context for these concepts generally use the term “analytics”; in some cases, the abbreviation DSA appears, meaning Data Science and Analytics.
This volume is the third draft articulation of computing-focused competencies for data science. It recognizes the inherent interdisciplinarity of data science and situates computing-specific competencies within the broader interdisciplinary space
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