---+ Computer Architecture ---++ Software Optimization Previous research work has identified memory bandwidth as the main bottleneck of the ubiquitous Sparse Matrix-Vector Multiplication kernel. To attack this problem, we aim at reducing the overall data volume of the algorithm. Typical sparse matrix representation schemes store only the non-zero elements of the matrix and employ additional indexing information to properly iterate over these elements. In this paper we propose two distinct compression methods targeting index and numerical values respectively. We perform a set of experiments on a large real-world matrix set and demonstrate that the index compression method can be applied successfully to a wide range of matrices. Moreover, the value compression method is able to achieve impressive speedups in a more limited, yet important, class of sparse matrices that contain a small number of distinct values. ---++ Operating Systems Providing scalable clustered storage in a cost-effective way depends on the availability of an efficient network block device (nbd) layer. We study the performance of gmblock, an nbd server over Myrinet utilizing a direct disk-to-NIC data path which bypasses the CPU and main memory bus. To overcome the architectural limitation of a low number of outstanding requests, we focus on overlapping read and network I/O for a single request, in order to improve throughput. To this end, we introduce the concept of synchronized send operations and present an implementation on Myrinet/GM, based on custom modifications to the NIC firmware and associated userspace library. Compared to a network block sharing system over standard GM and the base version of gmblock, our enhanced implementation supporting synchronized sends delivers 81% and 44% higher throughput for streaming block I/O, respectively.
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Topic revision: r4 - 2008-03-07 - VasileiosKarakasis
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