Investigation and development of implicit numerical methods for building energy simulation

A variety of building energy analysis and simulation tools are increasingly used to determine peak heating and cooling loads, size thermal plant, anticipate annual energy consumption and analyse thermal comfort. Numerical solution techniques are considered the most flexible for building energy simulation. When applied to the differential equations modelling energy flows in buildings, they give rise to a system of non-linear algebraic (difference) equations. In order to evaluate numerical methods for building energy simulation, the problem has been characterized mathematically and comprehensive test problems (equation sets) with these characteristics have been prepared. The principal attribute of the problem was found to be a stifiess ratio of the order of lo4. Candidate methods have been programmed and their outputs compared, in numerical experiments, with highly accurate (converged) solutions for the test problems. The accepted validation methods, empirical validation, analytical verification and inter-modal comparison were considered inappropriate. The first estimates total and not just numerical error, the second is too confined and the third lacks an absolute standard. The main evaluation parameter used was computational efficiency which is defined as accuracy attained per unit (computational) effort expended. An improved difference equation solver has been proposed and compared with the one used in the European reference model (ESP) and elsewhere. It was found to produce 27% less error than the currently used method. A fundamental method for estimating the pre-conditioning period of a building has been put forward in this part of the work. The trapezoidal rule (TR) is currently used in a number of building energy simulation packages including ESP. A known instability associated with the method is described and an implicit member of the Runge-Kutta family, possessing the necessary strong stability, has been shown, using the test problems, to be more efficient than TR by a factor of 4.27

A general framework to realize an abstract machine as an ILP processor with application to java

Ph.DDOCTOR OF PHILOSOPH

Performance counter-based strategies to improve data locality on multiprocessor systems: reordering and page migration techniques

In this dissertation we approach the study of Precise Event-Based Sampling (PEBS) techniques to improve the performance of applications on a NUMA, Itanium2-based system. We demonstrate that a low-cost, PEBS profiling can support strategies to improve the performance of an important group of computational and scientific codes in runtime. In addition, the accurate information provided by the new Event Adress Registers (EAR) of the Intel Itanium architecture helps foster the development of new data allocation strategies. Following this line, we have also developed a series of dynamic page migration PEBS strategies. Specifically, two problems are addressed: how to improve the performance of locality optimisation techniques for irregular codes in runtime, particularising for the Sparse Matrix-Vector product kernel, and how to develop strategies for dynamic page migration. To summarise, the main contributions of this dissertation are: 1. A study of the different factors that affect the performance, as well as data and thread allocation policies, in the FinisTerrae supercomputer, the target platform in which this thesis relies on. 2. The implementation of a performance model for FinisTerrae. 3. The development of hardware counter-based strategies to assist reordering techniques for irregular codes in order to reduce their cost and improve their behaviour. 4. The development of novel hardware counter-guided, dynamic page migration algorithms that take advantage of the new features provided by the PEBS. As a software contribution, we present a user-level page-migration framework to monitor, sample and control an application in runtime

Avion 2004-03-02

https://commons.erau.edu/avion/1996/thumbnail.jp

Just-in-time Hardware generation for abstracted reconfigurable computing

This thesis addresses the use of reconfigurable hardware in computing platforms, in order to harness the performance benefits of dedicated hardware whilst maintaining the flexibility associated with software. Although the reconfigurable computing concept is not new, the low level nature of the supporting tools normally used, together with the consequent limited level of abstraction and resultant lack of backwards compatibility, has prevented the widespread adoption of this technology. In addition, bandwidth and architectural limitations, have seriously constrained the potential improvements in performance. A review of existing approaches and tools flows is conducted to highlight the current problems being faced in this field. The objective of the work presented in this thesis is to introduce a radically new approach to reconfigurable computing tool flows. The runtime based tool flow introduces complete abstraction between the application developer and the underlying hardware. This new technique eliminates the ease of use and backwards compatibility issues that have plagued the reconfigurable computing concept, and could pave the way for viable mainstream reconfigurable computing platforms. An easy to use, cycle accurate behavioural modelling system is also presented, which was used extensively during the early exploration of new concepts and architectures. Some performance improvements produced by the new reconfigurable computing tool flow, when applied to both a MIPS based embedded platform, and the Cray XDl, are also presented. These results are then analyzed and the hardware and software factors affecting the performance increases that were obtained are discussed, together with potential techniques that could be used to further increase the performance of the system. Lastly a heterogenous computing concept is proposed, in which, a computer system, containing multiple types of computational resource is envisaged, each having their own strengths and weaknesses (e.g. DSPs, CPUs, FPGAs). A revolutionary new method of fully exploiting the potential of such a system, whilst maintaining scalability, backwards compatibility, and ease of use is also presented

An FPGA implementation of an investigative many-core processor, Fynbos : in support of a Fortran autoparallelising software pipeline

Includes bibliographical references.In light of the power, memory, ILP, and utilisation walls facing the computing industry, this work examines the hypothetical many-core approach to finding greater compute performance and efficiency. In order to achieve greater efficiency in an environment in which Moore’s law continues but TDP has been capped, a means of deriving performance from dark and dim silicon is needed. The many-core hypothesis is one approach to exploiting these available transistors efficiently. As understood in this work, it involves trading in hardware control complexity for hundreds to thousands of parallel simple processing elements, and operating at a clock speed sufficiently low as to allow the efficiency gains of near threshold voltage operation. Performance is there- fore dependant on exploiting a new degree of fine-grained parallelism such as is currently only found in GPGPUs, but in a manner that is not as restrictive in application domain range. While removing the complex control hardware of traditional CPUs provides space for more arithmetic hardware, a basic level of control is still required. For a number of reasons this work chooses to replace this control largely with static scheduling. This pushes the burden of control primarily to the software and specifically the compiler, rather not to the programmer or to an application specific means of control simplification. An existing legacy tool chain capable of autoparallelising sequential Fortran code to the degree of parallelism necessary for many-core exists. This work implements a many-core architecture to match it. Prototyping the design on an FPGA, it is possible to examine the real world performance of the compiler-architecture system to a greater degree than simulation only would allow. Comparing theoretical peak performance and real performance in a case study application, the system is found to be more efficient than any other reviewed, but to also significantly under perform relative to current competing architectures. This failing is apportioned to taking the need for simple hardware too far, and an inability to implement static scheduling mitigating tactics due to lack of support for such in the compiler

Washington University Record, October 4, 2002

https://digitalcommons.wustl.edu/record/1943/thumbnail.jp

Automating the construction of a complier heuristics using machine learning

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.Includes bibliographical references (p. 153-162).Compiler writers are expected to create effective and inexpensive solutions to NP-hard problems such as instruction scheduling and register allocation. To make matters worse, separate optimization phases have strong interactions and competing resource constraints. Compiler writers deal with system complexity by dividing the problem into multiple phases and devising approximate heuristics for each phase. However, to achieve satisfactory performance, developers are forced to manually tweak their heuristics with trial-and-error experimentation. In this dissertation I present meta optimization, a methodology for automatically constructing high quality compiler heuristics using machine learning techniques. This thesis describes machine-learned heuristics for three important compiler optimizations: hyperblock formation, register allocation, and loop unrolling. The machine-learned heuristics outperform (by as much as 3x in some cases) their state-of-the-art hand-crafted counterparts. By automatically collecting data and systematically analyzing them, my techniques discover subtle interactions that even experienced engineers would likely overlook. In addition to improving performance, my techniques can significantly reduce the human effort involved in compiler design.(cont.) Machine learning algorithms can design critical portions of compiler heuristics, thereby freeing the human designer to focus on compiler correctness. The progression of experiments I conduct in this thesis leads to collaborative compilation, an approach which enables ordinary users to transparently train compiler heuristics by running their applications as they normally would. The collaborative system automatically adapts itself to the applications in which a community of users is interested.by Mark W. Stephenson.Ph.D

Siirtoliipaisuarkkitehtuurin muuttuvanmittaisten käskyjen pakkaus

The Static Random-Access Memory (SRAM) modules used for embedded microprocessor devices consume a large portion of the whole system’s power. The memory module consumes static power on keeping awake and dynamic power on memory accesses. The power dissipation of the instruction memory can be limited by using code compression methods, which reduce the memory size. The compression may require the use of variable length instruction formats in the processor. The power-efficient design of variable length instruction fetch and decode units is challenging for static multiple-issue processors, because such architectures have simple hardware to begin with, as they aim for very low power consumption on embedded platforms. The power saved by using these compression approaches, which necessitate more complex logic, is easily lost on inefficient processor design. This thesis proposes an implementation for instruction template-based compression, its decompression and two instruction fetch design alternatives for variable length instruction encoding on Transport Triggered Architecture (TTA), a static multiple-issue exposed data path architecture. Both of the new fetch and decode units are integrated into the TTA-based Co-design Environment (TCE), which is a toolset for rapid designing and prototyping of processors based on TTA. The hardware description of the fetch units is verified on a register transfer level and benchmarked using the CHStone test suite. Furthermore, the fetch units are synthesized on a 40 nm standard cell Application Specific Integrated Circuit (ASIC) technology library for area, performance and power consumption measurements. The power cost of the variable length instruction support is compared to the power savings from memory reduction, which is evaluated using HP Labs’ CACTI tool. The compression approach reaches an average program size reduction of 44% at best with a set of test programs, and the total power consumption of the system is reduced. The thesis shows that the proposed variable length fetch designs are sufficiently low-power oriented for TTA processors to benefit from the code compression

An automated OpenCL FPGA compilation framework targeting a configurable, VLIW chip multiprocessor

Modern system-on-chips augment their baseline CPU with coprocessors and accelerators to increase overall computational capacity and power efficiency, and thus have evolved into heterogeneous systems. Several languages have been developed to enable this paradigm shift, including CUDA and OpenCL. This thesis discusses a unified compilation environment to enable heterogeneous system design through the use of OpenCL and a customised VLIW chip multiprocessor (CMP) architecture, known as the LE1. An LLVM compilation framework was researched and a prototype developed to enable the execution of OpenCL applications on the LE1 CPU. The framework fully automates the compilation flow and supports work-item coalescing to better utilise the CPU cores and alleviate the effects of thread divergence. This thesis discusses in detail both the software stack and target hardware architecture and evaluates the scalability of the proposed framework on a highly precise cycle-accurate simulator. This is achieved through the execution of 12 benchmarks across 240 different machine configurations, as well as further results utilising an incomplete development branch of the compiler. It is shown that the problems generally scale well with the LE1 architecture, up to eight cores, when the memory system becomes a serious bottleneck. Results demonstrate superlinear performance on certain benchmarks (x9 for the bitonic sort benchmark with 8 dual-issue cores) with further improvements from compiler optimisations (x14 for bitonic with the same configuration