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Computer-aided programming for multiprocessing systems
As both the number of processors and the complexity of problems to be solved increase, programming multiprocessing systems becomes more difficult and error-prone. This report discusses parallel models of computation and tools for computer-aided programming (CAP). Program development tools are necessary since programmers are not able to develop complex parallel programs efficiently. In particular, a CAP tool, named Hypertool, is described here. It performs scheduling and handles the communication primitive insertion automatically so that many errors are eliminated. It also generates the performance estimates and other program quality measures to help programmers in improving their algorithms and programs. Experiments have shown that up to a 300% performance improvement can be achieved by computer-aided programming
PinComm: characterizing intra-application communication for the many-core era
While the number of cores in both general purpose chip-multiprocessors (CMPs) and embedded Multi-Processor Systems-on-Chip (MPSoCs) keeps rising, on-chip communication becomes more and more important. In order to write efficient programs for these architectures, it is therefore necessary to have a good idea of the communication behavior of an application. We present a communication profiler that extracts this behavior from compiled, sequential C/C++ programs, and constructs a dynamic data-flow graph at the level of major functional blocks. It can also be used to view differences between program phases, such as different video frames, which allows both input- and phase-specific optimizations to be made. Finally, PinComm can visualize inter-thread communication in parallel programs, which can help in optimizing communication behavior and spotting communication-related performance bottlenecks
Execution models for mapping programs onto distributed memory parallel computers
The problem of exploiting the parallelism available in a program to efficiently employ the resources of the target machine is addressed. The problem is discussed in the context of building a mapping compiler for a distributed memory parallel machine. The paper describes using execution models to drive the process of mapping a program in the most efficient way onto a particular machine. Through analysis of the execution models for several mapping techniques for one class of programs, we show that the selection of the best technique for a particular program instance can make a significant difference in performance. On the other hand, the results of benchmarks from an implementation of a mapping compiler show that our execution models are accurate enough to select the best mapping technique for a given program
Scalable data abstractions for distributed parallel computations
The ability to express a program as a hierarchical composition of parts is an
essential tool in managing the complexity of software and a key abstraction
this provides is to separate the representation of data from the computation.
Many current parallel programming models use a shared memory model to provide
data abstraction but this doesn't scale well with large numbers of cores due to
non-determinism and access latency. This paper proposes a simple programming
model that allows scalable parallel programs to be expressed with distributed
representations of data and it provides the programmer with the flexibility to
employ shared or distributed styles of data-parallelism where applicable. It is
capable of an efficient implementation, and with the provision of a small set
of primitive capabilities in the hardware, it can be compiled to operate
directly on the hardware, in the same way stack-based allocation operates for
subroutines in sequential machines
S+Net: extending functional coordination with extra-functional semantics
This technical report introduces S+Net, a compositional coordination language
for streaming networks with extra-functional semantics. Compositionality
simplifies the specification of complex parallel and distributed applications;
extra-functional semantics allow the application designer to reason about and
control resource usage, performance and fault handling. The key feature of
S+Net is that functional and extra-functional semantics are defined
orthogonally from each other. S+Net can be seen as a simultaneous
simplification and extension of the existing coordination language S-Net, that
gives control of extra-functional behavior to the S-Net programmer. S+Net can
also be seen as a transitional research step between S-Net and AstraKahn,
another coordination language currently being designed at the University of
Hertfordshire. In contrast with AstraKahn which constitutes a re-design from
the ground up, S+Net preserves the basic operational semantics of S-Net and
thus provides an incremental introduction of extra-functional control in an
existing language.Comment: 34 pages, 11 figures, 3 table
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