Szárnyas Gábor (BME MIT): GraphBLAS: A linear algebraic approach for high-performance graph algorithms Designing efficient graph algorithms is challenging from both the theoretical and practical points of view. While the duality of graphs and sparse adjacency matrices is well-known, open-source graph processing systems have rarely used matrix-based programming models and researchers did not reach a consensus on the building blocks necessary for creating high-performance graph algorithms. The GraphBLAS initiative (launched in 2013) aims to define a standard to capture graph algorithms in the language of linear algebra - following the footsteps of the BLAS standard which, starting four decades ago, revolutionized scientific computing by defining constructs on dense matrices. In this talk, I give an overview of the GraphBLAS standard and its key components. First, I illustrate how matrix operations on various semirings correspond to the steps in graph algorithms. I then use these operations to present five distinct graph algorithms: BFS, shortest paths, clustering coefficient, PageRank, and community detection. I discuss the connection between sparse matrix multiplication operations and the family of worst-case optimal join algorithms (used for computing multiway join operations). Finally, I demonstrate the scalability of the GraphBLAS-based algorithms and list some open problems. Ha esetleg van magyarul nem beszélő érdeklődő, bátran jöhet, akkor  angolul lesz. Ha nincs, akkor magyarul.