1,045 research outputs found
Requirements for implementing real-time control functional modules on a hierarchical parallel pipelined system
Analysis of a robot control system leads to a broad range of processing requirements. One fundamental requirement of a robot control system is the necessity of a microcomputer system in order to provide sufficient processing capability.The use of multiple processors in a parallel architecture is beneficial for a number of reasons, including better cost performance, modular growth, increased reliability through replication, and flexibility for testing alternate control strategies via different partitioning. A survey of the progression from low level control synchronizing primitives to higher level communication tools is presented. The system communication and control mechanisms of existing robot control systems are compared to the hierarchical control model. The impact of this design methodology on the current robot control systems is explored
An Implementation of a Dual-Processor System on FPGA
In recent years, Field-Programmable Gate Arrays (FPGA) have evolved rapidly
paving the way for a whole new range of computing paradigms. On the other hand,
computer applications are evolving. There is a rising demand for a system that
is general-purpose and yet has the processing abilities to accommodate current
trends in application processing. This work proposes a design and
implementation of a tightly-coupled FPGA-based dual-processor platform. We
architect a platform that optimizes the utilization of FPGA resources and
allows for the investigation of practical implementation issues such as cache
design. The performance of the proposed prototype is then evaluated, as
different configurations of a uniprocessor and a dual-processor system are
studied and compared against each other and against published results for
common industry-standard CPU platforms. The proposed implementation utilizes
the Nios II 32-bit embedded soft-core processor architecture designed for the
Altera Cyclone III family of FPGAs
Design of a monitor for the debugging and development of multiprocessing process control systems : a thesis presented in partial fulfilment of the requirements for the degree of Master of Technology in Computing Technology at Massey University
This thesis describes the design of a general purpose tool for debugging and developing multimicroprocessor process control systems. With the decreasing pnce of computers, multimicroprocessors are increasingly being used for process control. However, the lack of published information on multiprocessing systems and distributed systems has meant that methodologies and tools for debugging and developing such systems have been slow to develop. The monitor designed here is system independent, a considerable advantage over other such tools that are currently available
Hyperswitch communication network
The Hyperswitch Communication Network (HCN) is a large scale parallel computer prototype being developed at JPL. Commercial versions of the HCN computer are planned. The HCN computer being designed is a message passing multiple instruction multiple data (MIMD) computer, and offers many advantages in price-performance ratio, reliability and availability, and manufacturing over traditional uniprocessors and bus based multiprocessors. The design of the HCN operating system is a uniquely flexible environment that combines both parallel processing and distributed processing. This programming paradigm can achieve a balance among the following competing factors: performance in processing and communications, user friendliness, and fault tolerance. The prototype is being designed to accommodate a maximum of 64 state of the art microprocessors. The HCN is classified as a distributed supercomputer. The HCN system is described, and the performance/cost analysis and other competing factors within the system design are reviewed
Many-Task Computing and Blue Waters
This report discusses many-task computing (MTC) generically and in the
context of the proposed Blue Waters systems, which is planned to be the largest
NSF-funded supercomputer when it begins production use in 2012. The aim of this
report is to inform the BW project about MTC, including understanding aspects
of MTC applications that can be used to characterize the domain and
understanding the implications of these aspects to middleware and policies.
Many MTC applications do not neatly fit the stereotypes of high-performance
computing (HPC) or high-throughput computing (HTC) applications. Like HTC
applications, by definition MTC applications are structured as graphs of
discrete tasks, with explicit input and output dependencies forming the graph
edges. However, MTC applications have significant features that distinguish
them from typical HTC applications. In particular, different engineering
constraints for hardware and software must be met in order to support these
applications. HTC applications have traditionally run on platforms such as
grids and clusters, through either workflow systems or parallel programming
systems. MTC applications, in contrast, will often demand a short time to
solution, may be communication intensive or data intensive, and may comprise
very short tasks. Therefore, hardware and software for MTC must be engineered
to support the additional communication and I/O and must minimize task dispatch
overheads. The hardware of large-scale HPC systems, with its high degree of
parallelism and support for intensive communication, is well suited for MTC
applications. However, HPC systems often lack a dynamic resource-provisioning
feature, are not ideal for task communication via the file system, and have an
I/O system that is not optimized for MTC-style applications. Hence, additional
software support is likely to be required to gain full benefit from the HPC
hardware
SKIRT: hybrid parallelization of radiative transfer simulations
We describe the design, implementation and performance of the new hybrid
parallelization scheme in our Monte Carlo radiative transfer code SKIRT, which
has been used extensively for modeling the continuum radiation of dusty
astrophysical systems including late-type galaxies and dusty tori. The hybrid
scheme combines distributed memory parallelization, using the standard Message
Passing Interface (MPI) to communicate between processes, and shared memory
parallelization, providing multiple execution threads within each process to
avoid duplication of data structures. The synchronization between multiple
threads is accomplished through atomic operations without high-level locking
(also called lock-free programming). This improves the scaling behavior of the
code and substantially simplifies the implementation of the hybrid scheme. The
result is an extremely flexible solution that adjusts to the number of
available nodes, processors and memory, and consequently performs well on a
wide variety of computing architectures.Comment: 21 pages, 20 figure
TensorFlow Enabled Genetic Programming
Genetic Programming, a kind of evolutionary computation and machine learning
algorithm, is shown to benefit significantly from the application of vectorized
data and the TensorFlow numerical computation library on both CPU and GPU
architectures. The open source, Python Karoo GP is employed for a series of 190
tests across 6 platforms, with real-world datasets ranging from 18 to 5.5M data
points. This body of tests demonstrates that datasets measured in tens and
hundreds of data points see 2-15x improvement when moving from the scalar/SymPy
configuration to the vector/TensorFlow configuration, with a single core
performing on par or better than multiple CPU cores and GPUs. A dataset
composed of 90,000 data points demonstrates a single vector/TensorFlow CPU core
performing 875x better than 40 scalar/Sympy CPU cores. And a dataset containing
5.5M data points sees GPU configurations out-performing CPU configurations on
average by 1.3x.Comment: 8 pages, 5 figures; presented at GECCO 2017, Berlin, German
Simulation of Multiprocessor System Scheduling
The speed and performance of computers have become a major concern today. Multiprocessor systems are introduced to share the work load between the processors. By sharing the work load among processors, the speed and efficiency of the system can be increased drastically. To share the workload properly between the processors in the multiprocessor system a proper scheduling algorithm is needed. Hence, one of the major factors that influence the speed and efficiency of the multiprocessor system is scheduling. In this thesis, the main focus is on the process scheduling for multiprocessor systems. The factors which influence scheduling and scheduling algorithms are discussed.
Based on this idea of sharing the load among processors in the multiprocessor system, a simulation model for scheduling in a symmetric multiprocessor system is developed in the Department of Digital and Computer systems at Tampere University of Technology. This model treats all the processors in the system equally by allocating equal processor time for all the processes in the task and also evaluates the total execution time of the system for processing an input job. The scheduling algorithm in this simulation model is based on the input processes priority. The necessity of scheduling in multiprocessor systems is elaborated.
The goal of this thesis is to analyse how process scheduling influences the speed of the multiprocessor system. Also, the difference in total execution time of the input jobs with different number of processors and capacity of the processors in the multiprocessor system is studied
- …