Sorting a list of input numbers is one of the most fundamental problems in the field of computer science in general and high-throughput database applications in particular. Although literature abounds with various flavors of sorting algorithms, different architectures call for customized implementations to achieve faster sorting times.This paper presents an efficient implementation and detailed analysis of MergeSort on current CPU architectures. Our SIMD implementation with 128-bit SSE is 3.3X faster than the scalar version. In addition, our algorithm performs an efficient multiway merge, and is not constrained by the memory bandwidth. Our multi-threaded, SIMD implementation sorts 64 million floating point numbers in less than 0.5 seconds on a commodity 4-core Intel processor. This measured performance compares favorably with all previously published results.Additionally, the paper demonstrates performance scalability of the proposed sorting algorithm with respect to certain salient architectural features of modern chip multiprocessor (CMP) architectures, including SIMD width and core-count. Based on our analytical models of various architectural configurations, we see excellent scalability of our implementation with SIMD width scaling up to 16X wider than current SSE width of 128-bits, and CMP core-count scaling well beyond 32 cores. Cycle-accurate simulation of Intel's upcoming x86 many-core Larrabee architecture confirms scalability of our proposed algorithm.
-To date, most Internet applications focus on providing information, interaction, and entertainment for humans. However, with the widespread deployment of networked, intelligent sensor technologies, an Internet of Things (IoT) is steadily evolving, much like the Internet decades ago. In the future, hundreds of billions of smart sensors and devices will interact with one another without human intervention, on a Machine-to-Machine (M2M) basis. They will generate an enormous amount of data at an unprecedented scale and resolution, providing humans with information and control of events and objects even in remote physical environments. The scale of the M2M Internet will be several orders of magnitude larger than the existing Internet, posing serious research challenges. This paper will provide an overview of challenges and opportunities presented by this new paradigm.
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