A neural network based tool for semi-automatic code transformation

A neural network based tool has been developed to assist in the process of code transformation. The tool offers advice on appropriate transformations within a knowledge-driven, semi-automatic parallelisation environment. We have identified the essential characteristics of codes relevant to loop transformations. A Kohonen network is used to discover structure in the characterised codes thus revealing new knowledge that may be brought to bear on the mapping between codes and transformations or transformation sequences. A transform selector based on this process has been developed and successfully applied to the parallelisation of sequential codes.

Continuous MLL-ENL expression is necessary to establish a "Hox Code" and maintain immortalization of hematopoietic progenitor cells

The t[(11;19)(p22;q23)] translocation, which gives rise to the MLL-ENL fusion protein, is commonly found in infant acute leukemias of both the myeloid and lymphoid lineage. To investigate the molecular mechanism of immortalization by MLL-ENL we established a Tet-regulatable system of MLL-ENL expression in primary hematopoietic progenitor cells. Immortalized myeloid cell lines were generated, which are dependent on continued MLL-ENL expression for their survival and proliferation. These cells either terminally differentiate or die when MLL-ENL expression is turned off with doxycycline. The expression profile of all 39 murine Hox genes was analyzed in these cells by real-time quantitative PCR. This analysis showed that loss of MLL-ENL was accompanied by a reduction in the expression of multiple Hoxa genes. By comparing these changes with Hox gene expression in cells induced to differentiate with granulocyte colony-stimulating factor, we show for the first time that reduced Hox gene expression is specific to loss of MLL-ENL and is not a consequence of differentiation. Our data also suggest that the Hox cofactor Meis-2 can substitute for Meis-1 function. Thus, MLL-ENL is required to initiate and maintain immortalization of myeloid progenitors and may contribute to leukemogenesis by aberrantly sustaining the expression of a "Hox code" consisting of Hoxa4 to Hoxa11.

Allocating transmission loss to loads and generators through complex power flow tracing

This paper presents a new method for complex power flow tracing that can be used for allocating the transmission loss to loads or generators. Two algorithms for upstream tracing (UST) and downstream tracing (DST) of the complex power are introduced. UST algorithm traces the complex power extracted by loads back to source nodes and assigns a fraction of the complex power flow through each line to each load. DST algorithm traces the output of the generators down to the sink nodes determining the contributions of each generator to the complex power flow and losses through each line. While doing so, active- and reactive-power flows as well as complex losses are considered simultaneously, not separately as most of the available methods do. Transmission losses are taken into consideration during power flow tracing. Unbundling line losses are carried out using an equation, which has a physical basis, and considers the coupling between active- and reactive-power flows as well as the cross effects of active and reactive powers on active and reactive losses. The tracing algorithms introduced can be considered direct to a good extent, as there is no need for exhaustive search to determine the flow paths as these are determined in a systematic way during the course of tracing. Results of application of the proposed method are also presented.

A method for determining generators’ shares in loads, line flows and losses

This paper presents a new method for calculating the individual generators’ shares in line flows, line losses and loads. The method is described and illustrated on active power flows, but it can be applied in the same way to reactive power flows. Starting from a power flow solution, the line flow matrix is formed. This matrix is used for identifying node types, tracing the power flow from generators downstream to loads, and to determine generators’ participation factors to lines and loads. Neither exhaustive search nor matrix inversion is required. Hence, the method is claimed to be the least computationally demanding amongst all of the similar methods.

A meta-heuristic approach to parallel code generation

The efficient generation of parallel code for multi-processor environments, is a large and complicated issue. Attempts to address this problem have always resulted in significant input from users. Because of constraints on user knowledge and time, the automation of the process is a promising and practically important research area. In recent years heuristic approaches have been used to capture available knowledge and make it available for the parallelisation process. Here, the introduction of a novel approach of neural network techniques is combined with an expert system technique to enhance the availability of knowledge to aid in the automatic generation of parallel code.