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Graph500 is a data intensive application for high performance computing and it is an increasingly important workload because graphs are a core part of most analytic applications. So far there is no work that examines if Graph500 is suitable for vectorization mostly due a lack of vector memory instructions for irregular memory accesses. The Xeon Phi is a(More)
Selecting an appropriate estimation method for a given technology and design is of crucial interest as the estimations guide future project and design decisions. The accuracy of the estimations of area, timing, and power (metrics of interest) depends on the phase of the design flow and the fidelity of the models. In this research, we use design space(More)
Mobile devices execute applications with diverse compute and performance demands. This paper proposes a general purpose processor that adapts the underlying hardware to a given workload. Existing mobile processors need to utilize more complex heterogeneous substrates to deliver the demanded performance. They incorporate different cores and specialized(More)
Vector architectures have been traditionally applied to the supercomputing domain with many successful incarnations. The energy efficiency and high performance of vector processors, as well as their applicability in other emerging domains, encourage pursuing further research on vector architectures. However, there is a lack of appropriate tools to perform(More)
This paper proposes a cost-effective technique that morphs the available cores of a low power chip multiprocessor (CMP) into an accelerator for data parallel (DLP) workloads. Instead of adding a special-purpose vector architecture as an accelerator, our technique leverages the resources of each CMP core to mimic the functionality of a vector processor. The(More)
In the low-end mobile processor market, power, energy and area budgets are significantly lower than in other markets (e.g. servers or high-end mobile markets). It has been shown that vector processors are a highly energy-efficient way to increase performance; however adding support for them incurs area and power overheads that would not be acceptable for(More)
In the low-end mobile processor market, power, energy and area budgets are significantly lower than in the server/desktop/laptop/high-end mobile markets. It has been shown that vector processors are a highly energy-efficient way to increase performance but adding support for them incurs area and power overheads that could not be acceptable for low-end(More)