MURAC: A unified machine model for heterogeneous computers

Includes bibliographical referencesHeterogeneous computing enables the performance and energy advantages of multiple distinct processing architectures to be efficiently exploited within a single machine. These systems are capable of delivering large performance increases by matching the applications to architectures that are most suited to them. The Multiple Runtime-reconfigurable Architecture Computer (MURAC) model has been proposed to tackle the problems commonly found in the design and usage of these machines. This model presents a system-level approach that creates a clear separation of concerns between the system implementer and the application developer. The three key concepts that make up the MURAC model are a unified machine model, a unified instruction stream and a unified memory space. A simple programming model built upon these abstractions provides a consistent interface for interacting with the underlying machine to the user application. This programming model simplifies application partitioning between hardware and software and allows the easy integration of different execution models within the single control ow of a mixed-architecture application. The theoretical and practical trade-offs of the proposed model have been explored through the design of several systems. An instruction-accurate system simulator has been developed that supports the simulated execution of mixed-architecture applications. An embedded System-on-Chip implementation has been used to measure the overhead in hardware resources required to support the model, which was found to be minimal. An implementation of the model within an operating system on a tightly-coupled reconfigurable processor platform has been created. This implementation is used to extend the software scheduler to allow for the full support of mixed-architecture applications in a multitasking environment. Different scheduling strategies have been tested using this scheduler for mixed-architecture applications. The design and implementation of these systems has shown that a unified abstraction model for heterogeneous computers provides important usability benefits to system and application designers. These benefits are achieved through a consistent view of the multiple different architectures to the operating system and user applications. This allows them to focus on achieving their performance and efficiency goals by gaining the benefits of different execution models during runtime without the complex implementation details of the system-level synchronisation and coordination

hArtes: Hardware-Software Codesign for Heterogeneous Multicore Platforms

Developing heterogeneous multicore platforms requires choosing the best hardware configuration for mapping the application, and modifying that application so that different parts execute on the most appropriate hardware component. The hArtes toolchain provides the option of automatic or semi-automatic support for this mapping. During test and validation on several computation-intensive applications, hArtes achieved substantial speedups and drastically reduced development times

Radiation safety based on the sky shine effect in reactor

In the reactor operation, neutrons and gamma rays are the most dominant radiation. As protection, lead and concrete shields are built around the reactor. However, the radiation can penetrate the water shielding inside the reactor pool. This incident leads to the occurrence of sky shine where a physical phenomenon of nuclear radiation sources was transmitted panoramic that extends to the environment. The effect of this phenomenon is caused by the fallout radiation into the surrounding area which causes the radiation dose to increase. High doses of exposure cause a person to have stochastic effects or deterministic effects. Therefore, this study was conducted to measure the radiation dose from sky shine effect that scattered around the reactor at different distances and different height above the reactor platform. In this paper, the analysis of the radiation dose of sky shine effect was measured using the experimental metho

Object oriented execution model (OOM)

This paper considers implementing the Object Oriented Programming Model directly in the hardware to serve as a base to exploit object-level parallelism, speculation and heterogeneous computing. Towards this goal, we present a new execution model called Object Oriented execution Model - OOM - that implements the OO Programming Models. All OOM hardware structures are objects and the OOM Instruction Set directly utilizes objects while hiding other complex hardware structures. OOM maintains all high-level programming language information until execution time. This enables efficient extraction of available parallelism in OO serial code at execution time with minimal compiler support. Our results show that OOM utilizes the available parallelism better than the OoO (Out-of-Order) modelPeer ReviewedPostprint (published version

Automatic generation and testing of application specific hardware accelerators on a new reconfigurable OpenSPARC platform

Specific hardware customization for scientific applications has shown a big potential to address the current holy grail in computer architecture: reducing power consumption while increasing performance. In particular, the automatic generation of domain-specific accelerators for General- Purpose Processors (GPPs) is an active field of research to the point that different leading hardware design companies (e.g. Intel, ARM) are announcing commercial platforms that integrate GPPs and FPGAs. In this paper we present a new framework with a holistic approach that addresses the challenge of design exploration of specific application accelerators. Our work focuses on a target platform consisting of a GPP with a reconfigurable functional unit. The framework includes a reconfigurable 1-core 1-thread OpenSPARC with a new programmable specific purpose unit (SPU) inside the OpenSPARC core. In order to program the SPU we have developed an automatic toolchain that profiles an application and discovers its main computing bottlenecks. With that information our toolchain is able to both design hardware specific accelerators that can be automatically mapped in the aforementioned SPU, and generate the binary code necessary to run the application using those accelerators. The OpenSPARC with the new specific application accelerators, defined in a Hardware Description Language, can then be executed and measured. Still awaiting further development, nowadays our framework is a proof-of-concept that shows that this kind of systems can be developed and programmed as easily as a GPP. In a near future it would be the source of very interesting information about the capabilities and drawbacks of those mixed GPP-FPGA systems.Postprint (published version