Lauro Beltrão Costa

Learn More
eScience is rapidly changing the way we do research. As a result, many research labs now need non-trivial computational power. Grid and voluntary computing are well-established solutions for this need. However, not all labs can effectively benefit from these technologies. In particular, small and medium research labs (which are the majority of the labs in(More)
Large, real-world graphs are famously difficult to process efficiently. Not only they have a large memory footprint but most graph processing algorithms entail memory access patterns with poor locality, data-dependent parallelism, and a low compute-to- memory access ratio. Additionally, most real-world graphs have a low diameter and a highly heterogeneous(More)
The increasing scale and wealth of inter-connected data, such as those accrued by social network applications, demand the design of new techniques and platforms to efficiently derive actionable knowledge from large-scale graphs. However, large real-world graphs are famously difficult to process efficiently. Not only they have a large memory footprint, but(More)
We here discuss how to run Bag-of-Tasks applications (those parallel applications whose tasks are independent) on computational grids. Bag-of-Tasks applications are both relevant and amendable for execution on grids. However, few users currently execute their Bag-of-Tasks applications on grids. We investigate the reason for this state of affairs and(More)
Graph processing has gained renewed attention. The increasing large scale and wealth of connected data, such as those accrued by social network applications, demand the design of new techniques and platforms to efficiently derive actionable information from large scale graphs. Hybrid systems that host processing units optimized for both fast sequential(More)
Large scale grid computing systems may provide multitudinous services, from different providers, whose quality of service will vary. Moreover, services are deployed and undeployed in the grid with no central coordination. Thus, to find out the most suitable service to fulfill their needs, or to find the most suitable set of resources on which to deploy(More)
The energy costs of running computer systems are a growing concern: for large data centers, recent estimates put these costs higher than the cost of hardware itself. As a consequence, energy efficiency has become a pervasive theme for designing, deploying, and operating computer systems. This paper evaluates the energy trade-offs brought by data(More)
In this paper we discuss the difficulties involved in the scheduling of applications on computational grids. We highlight two main sources of difficulties: 1) the size of the grid rules out the possibility of using a centralized scheduler; 2) since resources are managed by different parties, the scheduler must consider several different policies. Thus, we(More)
MyGrid is a complete grid solution for running Bag-of-Tasks applications (i.e. parallel applications whose tasks are independent) over whatever resources are available to the user. MyGrid middleware empowers users to interoperate with heterogeneous computational resources across geographic and administrative boundaries. Due to MyGrid’s flexible(More)
This paper investigates the power, energy, and performance characteristics of large-scale graph processing on hybrid (i.e., CPU and GPU) single-node systems. Graph processing can be accelerated on hybrid systems by properly mapping the graph-layout to processing units, such that the algorithmic tasks exercise each of the units where they perform best.(More)