Tiled Algorithms for Matrix Computations on Multicore Architectures

The current computer architecture has moved towards the multi/many-core structure. However, the algorithms in the current sequential dense numerical linear algebra libraries (e.g. LAPACK) do not parallelize well on multi/many-core architectures. A new family of algorithms, the tile algorithms, has recently been introduced to circumvent this problem. Previous research has shown that it is possible to write efficient and scalable tile algorithms for performing a Cholesky factorization, a (pseudo) LU factorization, and a QR factorization. The goal of this thesis is to study tiled algorithms in a multi/many-core setting and to provide new algorithms which exploit the current architecture to improve performance relative to current state-of-the-art libraries while maintaining the stability and robustness of these libraries.Comment: PhD Thesis, 2012 http://math.ucdenver.ed

FYVE-Dependent Endosomal Targeting of an Arrestin-Related Protein in Amoeba

International audienceBACKGROUND: Visual and β-arrestins are scaffolding proteins involved in the regulation of receptor-dependent intracellular signaling and their trafficking. The arrestin superfamilly includes several arrestin domain-containing proteins and the structurally related protein Vps26. In Dictyostelium discoideum, the arrestin-domain containing proteins form a family of six members, namely AdcA to -F. In contrast to canonical arrestins, Dictyostelium Adc proteins show a more complex architecture, as they possess, in addition to the arrestin core, other domains, such as C2, FYVE, LIM, MIT and SAM, which potentially mediate selective interactions with either lipids or proteins. METHODOLOGY AND PRINCIPAL FINDINGS: A detailed analysis of AdcA has been performed. AdcA extends on both sides of the arrestin core, in particular by a FYVE domain which mediates selective interactions with PI(3)P, as disclosed by intrinsic fluorescence measurements and lipid overlay assays. Localization studies showed an enrichment of tagged- and endogenous AdcA on the rim of early macropinosomes and phagosomes. This vesicular distribution relies on a functional FYVE domain. Our data also show that the arrestin core binds the ADP-ribosylation factor ArfA, the unique amoebal Arf member, in its GDP-bound conformation. SIGNIFICANCE: This work describes one of the 6 arrestin domain-containing proteins of Dictyostelium, a novel and atypical member of the arrestin clan. It provides the basis for a better understanding of arrestin-related protein involvement in trafficking processes and for further studies on the expanding roles of arrestins in eukaryotes

Analysis of the key elements of FFAT-like motifs identifies new proteins that potentially bind VAP on the ER, including two AKAPs and FAPP2.

Two phenylalanines (FF) in an acidic tract (FFAT)-motifs were originally described as having seven elements: an acidic flanking region followed by 6 residues (EFFDA-E). Such motifs are found in several lipid transfer protein (LTP) families, and they interact with a protein on the cytosolic face of the ER called vesicle-associated membrane protein-associated protein (VAP). Mutation of which causes ER stress and motor neuron disease, making it important to determine which proteins bind VAP. Among other proteins that bind VAP, some contain FFAT-like motifs that are missing one or more of the seven elements. Defining how much variation is tolerated in FFAT-like motifs is a preliminary step prior to the identification of the full range of VAP interactors

Performance Optimization and Modeling of Blocked Sparse Kernels

International audienceWe present a method for automatically selecting optimal implementations of sparse matrix-vector operations. Our software “AcCELS” (Accelerated Compress-storage Elements for Linear Solvers) involves a setup phase that probes machine characteristics, and a run-time phase where stored characteristics are combined with a measure of the actual sparse matrix to find the optimal kernel implementation. We present a performance model that is shown to be accurate over a large range of matrices