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We propose a tightly-coupled, multi-core cluster architecture with shared, variation-tolerant, and accuracy-reconfigurable floating-point units (FPUs). The resilient shared-FPUs dynamically characterize FP pipeline vulnerability (FPV) and expose it as metadata to a software scheduler for reducing the cost of error correction. To further reduce this cost, our programming and runtime environment also supports controlled approximate computation through a combination of design-time and runtime techniques. We provide OpenMP extensions (as custom directives) for FP computations to specify parts of a program that can be executed approximately. We use a profiling technique to identify tolerable error significance and error rate thresholds in error-tolerant image processing applications. This information guides an application-driven hardware FPU synthesis and optimization design flow to generate efficient FPUs. At …