Theses - Dept. of Electrical Engineering and Computer Sciences
http://hdl.handle.net/1721.1/7599
2015-07-23T01:21:45ZA sampling technique based on LDPC codes
http://hdl.handle.net/1721.1/97821
A sampling technique based on LDPC codes
Zhang, Xuhong, S.M. Massachusetts Institute of Technology
Given an inference problem, it is common that exact inference algorithms are computationally intractable and one has to resort to approximate inference algorithms. Monte Carlo methods, which rely on repeated sampling of the target distribution to obtain numerical results, is a powerful and popular way to tackle difficult inference problems. In order to use Monte Carlo methods, a good sampling scheme is vital. This thesis aims to propose a new sampling scheme based on Low Density Parity Check codes and compare it with existing sampling techniques. The proposed sampling scheme works for discrete variables only, but makes no further assumption of the structure of target distribution. The main idea of the proposed sampling method relies on the concept of typicality. By definition, a strong typical sequence with respect to a distribution can closely approximate the distribution. In other words, if we can find a strong typical sequence, the symbols in the sequence can be used as samples from the distribution. According to asymptotic analysis, the set of typical sequences dominates the probability and all typical sequences are roughly equi-probable. Thus samples from the distribution can be obtained by associating each typical sequence with an index, uniformly randomly picking an index, and finding the typical sequence that corresponds to the chosen index. The symbols in that sequence are the desired samples. To simulate this process in practice, an LDPC code is introduced. Its parity check values are uniformly randomly generated, and can be regarded as the index. Then we look for the most likely sequence that satisfies all the parity checks, and it will be proved that this sequence is a typical one with high probability if the LDPC has appropriate rate. If the most likely sequence found is a typical one, it can be regarded as the one corresponding to the chosen index. In practice, finding the most likely sequence can be computationally intractable. Thus Belief Propagation algorithm is implemented to perform approximate simulation of the sampling process. The proposed LDPC-based sampling scheme is formally defined first. After proving its correctness under maximum-likelihood simulation, we empirically examine the performance of the scheme on several distributions, namely Markov chain sources, Single loop sources, and 2-Dimensional Ising models. The results show that the proposed scheme can produce good quality samples for the aforementioned distributions.
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.; Cataloged from PDF version of thesis.; Includes bibliographical references (pages 111-113).
2015-01-01T00:00:00ZAn evaluation of concurrency control with one thousand cores
http://hdl.handle.net/1721.1/97820
An evaluation of concurrency control with one thousand cores
Yu, Xiangyao
Computer architectures are moving towards an era dominated by many-core machines with dozens or even hundreds of cores on a single chip. This unprecedented level of on-chip parallelism introduces a new dimension to scalability that current database management systems (DBMSs) were not designed for. In particular, as the number of cores increases, the problem of concurrency control becomes extremely challenging. With hundreds of threads running in parallel, the complexity of coordinating competing accesses to data will likely diminish the gains from increased core counts. To better understand just how unprepared current DBMSs are for future CPU architectures, we performed an evaluation of concurrency control for on-line transaction processing (OLTP) workloads on many-core chips. We implemented seven concurrency control algorithms on a main-memory DBMS and using computer simulations scaled our system to 1024 cores. Our analysis shows that all algorithms fail to scale to this magnitude but for different reasons. In each case, we identify fundamental bottlenecks that are independent of the particular database implementation and argue that even state-of-the-art DBMSs suffer from these limitations. We conclude that rather than pursuing incremental solutions, many-core chips may require a completely redesigned DBMS architecture that is built from ground up and is tightly coupled with the hardware.
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.; Cataloged from PDF version of thesis.; Includes bibliographical references (pages 71-75).
2015-01-01T00:00:00ZMethods enabling interactive customization of fabricable objects by non-professionals
http://hdl.handle.net/1721.1/97819
Methods enabling interactive customization of fabricable objects by non-professionals
Shugrina, Maria D
This thesis addresses the problem of allowing casual users to customize the design of 3D printable objects while maintaining their validity. This work defines Fab Form as a representation formalizing the requirements for such designs: 1) the user should have a small number of intuitive parameters that allow customization; 2) the designs should maintain their valid state as 3D printable objects; and 3) the customization process should be interactive. To achieve these, my solution separates Fab Form evaluation into a precomputation stage and a runtime stage. Parts of the geometry and design validity (such as manufacturability) are evaluated and stored in the precomputation stage by adaptively sampling the design space. At runtime the remainder of the evaluation is performed. This allows interactive navigation in the valid regions of the design space using an automatically generated Web user interface. This approach is evaluated by converting several parametric models into corresponding Fab Forms.
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.; Cataloged from PDF version of thesis.; Includes bibliographical references (pages 63-66).
2015-01-01T00:00:00ZA novel inference algorithm on graphical model
http://hdl.handle.net/1721.1/97818
A novel inference algorithm on graphical model
Pu, Yewen
We present a framework for approximate inference that, given a factor graph and a subset of its variables, produces an approximate marginal distribution over these variables with bounds. The factors of the factor graph are abstracted as as piecewise polynomial functions with lower and upper bounds, and a variant of the variable elimination algorithm solves the inference problem over this abstraction. The resulting distributions bound quantifies the error between it and the true distribution. We also give a set of heuristics for improving the bounds by further refining the binary space partition trees.
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.; Cataloged from PDF version of thesis.; Includes bibliographical references (pages 57-58).
2015-01-01T00:00:00Z