The power of restricted quantum computational models

Restricted models of quantum computation are ones that have less power than a universal quantum computer. We studied the consequences of removing particular properties from a universal quantum computer to discover whether those resources were important.In the first part of the thesis we studied universal quantum computers which are implemented using Clifford gates, adaptive measurements, and magic states. The Gottesman–Knill theorem shows that circuits in this form which do not use magic states can be simulated by a classical computer. We extended this result to show that all circuits in this form can be partially simulated; the same computation can be implemented using a smaller quantum computer with the assistance of some polynomial time classical computation. We also identified a subclass of these computations that can be shown to not be entirely classically simulated by any method, given certain complexity theoretic assumptions are true.In the next part of the thesis we examine the role of entanglement in noisy quantum computations. Entanglement is necessary for noiseless quantum computers to have any quantum advantage, but it is not known whether the same is true for mixed state quantum computers. We show that entanglement, unexpectedly, does play a crucial role in the most well known mixed state computer: the one clean qubit model.Finally, we investigate how closely classical simulation is related to another idea of classicality.This notion captures how easily the final state of a computation can be learnt, given samples of measurements from it. We find an extra condition under which a circuit that is classically simulable is also efficiently learnable

RowCore: A Processing-Near-Memory Architecture for Big Data Machine Learning

The technology-push of die stacking and application-pull of Big Data machine learning (BDML) have created a unique opportunity for processing-near-memory (PNM). This paper makes four contributions: (1) While previous PNM work explores general MapReduce workloads, we identify three workload characteristics: (a) irregular-and-compute-light (i.e., perform only a few operations per input word which include data-dependent branches and indirect memory accesses); (b) compact (i.e., the computation has a small intermediate live data and uses only a small amount of contiguous input data); and (c) memory-row-dense (i.e., process the input data without skipping over many bytes). We show that BDMLs have or can be transformed to have these characteristics which, except for irregularity, are necessary for bandwidth- and energyefficient PNM, irrespective of the architecture. (2) Based on these characteristics, we propose RowCore, a row-oriented PNM architecture, which (pre)fetches and operates on entire memory rows to exploit BDMLs’ row-density. Instead of this row-centric access and compute-schedule, traditional architectures opportunistically improve row locality while fetching and operating on cache blocks. (3) RowCore employs well-known MIMD execution to handle BDMLs’ irregularity, and sequential prefetch of input data to hide memory latency. In RowCore, however, one corelet prefetches a row for all the corelets which may stray far from each other due to their MIMD execution. Consequently, a leading corelet may prematurely evict the prefetched data before a lagging corelet has consumed the data. RowCore employs novel cross-corelet flow-control to prevent such eviction. (4) RowCore further exploits its flow-controlled prefetch for frequency scaling based on novel coarse-grain compute-memory rate-matching which decreases (increases) the processor clock speed when the prefetch buffers are empty (full). Using simulations, we show that RowCore improves performance and energy, by 135% and 20% over a GPGPU with prefetch, and by 35% and 34% over a multicore with prefetch, when all three architectures use the same resources (i.e., number of cores, and on-processor-die memory) and identical diestacking (i.e., GPGPUs/multicores/RowCore and DRAM)

Architectural Support for Operating System-Driven CMP Cache Management

The role of the operating system (OS) in managing shared resources such as CPU time, memory, peripherals, and even energy is well motivated and understood [22]. Unfortu- nately, one key resource|lower-level shared cache in chip multi-processors|is commonly managed purely in hardware by rudimentary replacement policies such as least-recently- used (LRU). The rigid nature of the hardware cache manage- ment policy poses a serious problem since there is no single best cache management policy across all sharing scenarios. For example, the cache management policy for a scenario where applications from a single organization are running under \best effort performance expectation is likely to be different from the policy for a scenario where applications from competing business entities (say, at a third party data center) are running under a minimum service level expecta- tion. When it comes to managing shared caches, there is an inherent tension between exibility and performance. On one hand, managing the shared cache in the OS offers immense policy exibility since it may be implemented in soft- ware. Unfortunately, it is prohibitively expensive in terms of performance for the OS to be involved in managing tempo- rally fine-grain events such as cache allocation. On the other hand, sophisticated hardware-only cache management tech- niques to achieve fair sharing or throughput maximization have been proposed. But they offer no policy exibility. This paper addresses this problem by designing architec- tural support for OS to effciently manage shared caches with a wide variety of policies. Our scheme consists of a hard- ware cache quota management mechanism, an OS interface and a set of OS level quota orchestration policies. The hard- ware mechanism guarantees that OS-specifed quotas are en- forced in shared caches, thus eliminating the need for (and the performance penalty of) temporally fine-grained OS in- tervention. The OS retains policy exibility since it can tune the quotas during regularly scheduled OS interventions. We demonstrate that our scheme can support a wide range of policies including policies that provide (a) passive per- formance differentiation, (b) reactive fairness by miss-rate equalization and (c) reactive performance differentiation

Evaluation of common risk factors of acne in teenagers in Batticaloa district

Acne, or acne vulgaris, is a common skin problem that starts when oil and dead skin cells obstruct the pores. It is leads to psychological dissatisfaction of personality specially among teenagers and adolescents all over the world, including Sri Lanka. In the recent years concern raised regarding acne without gender difference, because people like to be pretty and attractive in the society. Furthermore, majority of the school students are worried about the impact of acne as they are prone to suffer by acne and they naturally feel to be pretty because of their young stage and psycho social believes and thoughts. Therefore, this study was intended to recognize and evaluate the risk factors of acne among school teenagers of Batticaloa district. Respondents of the study included the students from four leading schools in the Batticaloa during the study period. Data collected by interviewer administered questionnaire with the permission of relevant principals of the school. Analysis of data performed by statistical software (SPSS 16.0) and p value <0.05 was considered as significant for all analysis. Majority of participant were Tamil (141=73.44%) ethnic group and most of them resided at urban 136 (70.83%) local authority. The skin type of more than half of the respondents was oily. Onset age of acne lesions for many respondents (39=20.31%) was 16 years. Almost most of them (187=97.40%) had the acne lesion on the face. Acne marks significantly (X2=38.342, p=0.000) leads to major psychological worries on males compared to female students. Food habit with oily meals had significant association to the development of acne, (X2=58.521, p=0.000). Food habit, Body weight, types of skin were identified as the most significant risk factors. Marks of acne is the very serious end results and which has the significant impact on formation of psychological problems among the students specifically in males