Convolutional neural networks (CNNs) have proven to be a disruptive technology in most
vision, speech and image processing tasks. Given their ubiquitous acceptance, the research …

Abstract Several studies in Bioinformatics, Computational Biology and Systems Biology rely
on the definition of physico-chemical or mathematical models of biological systems at …

Develo** high performance embedded vision applications requires balancing run-time
performance with energy constraints. Given the mix of hardware accelerators that exist for …

This paper presents and characterizes Rodinia, a benchmark suite for heterogeneous
computing. To help architects study emerging platforms such as GPUs (Graphics Processing …

We evaluate the power and performance of the Rodinia benchmark suite using the Altera
SDK for OpenCL targeting a Stratix V FPGA against a modern CPU and GPU. We study …

The recently released Rodinia benchmark suite enables users to evaluate heterogeneous
systems including both accelerators, such as GPUs, and multicore CPUs. As Rodinia sees …

With the emergence of accelerator devices such as multicores, graphics-processing units
(GPUs), and field-programmable gate arrays (FPGAs), application designers are confronted …

This paper aims to better understand the performance differences between FPGAs and
GPUs. We intentionally begin with a widely used GPU-friendly benchmark suite, Rodinia …

Node level heterogeneous architectures have become attractive during the last decade for
several reasons: compared to traditional symmetric CPUs, they offer high peak performance …

To extend the exponential performance scaling of future chip multiprocessors, improving
energy efficiency has become a first-class priority. Single-chip heterogeneous computing …