16194916
Cross-Situational Learning: A Mathematical Approach
We present a mathematical model of cross-situational learning, in which we quantify the learnability of words and vocabularies. We find that high levels of uncertainty are not an impediment to learning single words or whole vocabulary systems, as long as the level of uncertainty is somewhat lower than the total number of meanings in the system. We further note that even large vocabularies are learnable through cross-situational learning.
7048039
Establishing Communication Systems without Explicit Meaning Transmission
This paper investigates the development of experience-based meaning creation and explores the problem of establishing successful communication systems in a population of agents. The aim of the work is to investigate how such systems can develop, without reliance on phenomena not found in actual human language learning, such as the explicit transmission of meaning or the provision of reliable error feedback to guide learning. Agents develop individual, distinct meaning structures, and although they can communicate despite this, communicative success is closely related to the proportion of shared lexicalised meaning, and the communicative systems have a large degree of redundant synonymy.
18711767
Semantic Generalisation and the Inference of Meaning
In this paper, a computational model of a successful negotiated communication system is presented, in which language agents develop their own meanings in response to their environment and attempt to infer the meanings of others’ utterances. The inherent uncertainty in the process of meaning inference in the system leads to variation in the agents’ internal semantic representations, which then itself drives language change in the form of semantic generalisation.
16044004
Intelligent Meaning Creation in a Clumpy World Helps Communication
This article investigates the problem of how language learners decipher what words mean. In many recent models of language evolution, agents are provided with innate meanings a priori and explicitly transfer them to each other as part of the communication process. By contrast, I investigate how successful communication systems can emerge without innate or transferable meanings, and show that this is dependent on the agents developing highly synchronized conceptual systems. I present experiments with various cognitive, communicative, and environmental factors which affect the likelihood of agents achieving meaning synchronization and demonstrate that an intelligent meaning creation strategy in a clumpy world leads to the highest level of meaning similarity between agents.
39170769
Multiprogramming and Memory Contention
We study memory contention during multiprogramming when programs are free to compete for page frames. A random walk between the possible partitions of memory over the set of active programs is used to model memory contention and calculate throughput. Our model of contention takes into account program characteristics by using miss ratio curves, and also considers memory size and page fetch latency. With the aid of numerous trace-driven simulations, we are able to verify our model, finding good agreement both in the observed distribution of memory among competing programs and in CPU utilization. We find that for high ratios of secondary to primary memory access time and under conditions of high memory contention, small programs with compact working sets are able to run with far less than expected interference from larger, more diffuse programs. In the case of multiprogramming the same program several times, we find that observed partition distributions are not necessarily even and that higher than expected levels of CPU use are observed. Lower ratios of access time are found to yield different results; programs compete on a more even basis and partition memory relatively more evenly than with higher ratios.
8448410
Measuring the Performance of Multimedia Instruction Sets
Many microprocessor instruction sets include instructions for accelerating multimedia applications such as DVD playback, speech recognition, and 3D graphics. Despite general agreement on the need to support this emerging workload, there are considerable differences between the instruction sets that have been designed to do so. In this paper, we study the performance of five instruction sets on kernels extracted from a broad multimedia workload. We compare the performance of contemporary implementations of each extension against each other as well as to the original compiled C performance. From our analysis, we determine how well multimedia workloads map to current instruction sets, noting what was useful and what was not. We also propose two enhancements: fat subwords and strided memory operations.
2002086
Exploration of heterogeneous reconfigurable architectures
In contrast to early reconfigurable hardware, modern reconfigurable devices consist of a mixture of heterogeneous components. The heterogeneous components introduced in recent devices are both line and coarse-grain in their nature, and are primarily aimed at improving the speed, power consumption and area metrics of target designs. The aim of this PhD project is to look at analytical ways of exploring the design space of modern reconfigurable hardware. By automatically generating architectures and estimating benchmark performance, linear programming can eliminate architectural possibilities in an efficient way, meaning that a large number of different architectures can be examined in a fast and optimal manner.
36108373
Machine Characterization Based on an Abstract High-Level Language Machine
Measurements are presented for a large number of machines ranging from small workstations to supercomputers. The authors combine these measurements into groups of parameters which relate to specific aspects of the machine implementation, and use these groups to provide overall machine characterizations. The authors also define the concept of pershapes, which represent the level of performance of a machine for different types of computation. A metric based on pershapes is introduced that provides a quantitative way of measuring how similar two machines are in terms of their performance distributions. The metric is related to the extent to which pairs of machines have varying relative performance levels depending on which benchmark is used. >
2203322
Debugging sequential circuits using Boolean satisfiability
Logic debugging of today's complex sequential circuits is an important problem. In this paper, a logic debugging methodology for multiple errors in sequential circuits with no state equivalence is developed. The proposed approach reduces the problem of debugging to an instance of Boolean satisfiability. This formulation takes advantage of modern Boolean satisfiability solvers that handle large circuits in a computationally efficient manner. An extensive suite of experiments with large sequential circuits confirm the robustness and efficiency of the proposed approach. The results further suggest that Boolean satisfiability provides an effective platform for sequential logic debugging.