D2.5: Semantic specication for libraries

This document describes the deliverable D2.5 named Semantic specication for libraries. In document we present dierent mechanisms for specifying the semantic properties of libraries in generic terms. We explore two dierent alternative specications: axiom based and compiletime contracts. First mechanism Continue reading D2.5: Semantic specication for libraries

D6.3: Dynamic runtimes with auto-tuning capabilities

The REPARA Project aims to deploy software kernels of a sequential application written in C++ in a parallel heterogeneous platform by using static or dynamic scheduling and mapping techniques with the objective to improve both the performance and the energy Continue reading D6.3: Dynamic runtimes with auto-tuning capabilities

D5.4: Reconfigurable hardware integration into runtime engines

The REPARA Project aims to provide a uniform programming interface for applications on parallel heterogeneous platforms to improve both the performance, as well as the energy efficiency. Field-programmable gate arrays (FPGAs) are characterized by their potential for deep spatial parallelism Continue reading D5.4: Reconfigurable hardware integration into runtime engines

D5.2: Target platform for stand-alone hw execution and library of optimized module

The Repara Project targets the utilization of parallel heterogeneous hardware platforms such as GPGPUs, DSPs or FPGAs within a common design flow. Enhancements in terms of energy efficiency as well as performance shall be achieved by executing individual parts of Continue reading D5.2: Target platform for stand-alone hw execution and library of optimized module

D6.2: Dynamic runtimes for heterogeneous platforms

The REPARA Project aims to deploy software kernels of a sequential application written in C++ in parallel heterogeneous platforms by using static or dynamic scheduling and mapping techniques in order to improve both the performance and the energy efficiency. The Continue reading D6.2: Dynamic runtimes for heterogeneous platforms

D7.2: Detailed quantitative performance and energy models

In this document, we describe a method for deriving detailed quantitative models for predicting performance, power, and energy consumption based on source code software metrics, with a special focus on recongurable hardware. The models are built by employing various statistical and Continue reading D7.2: Detailed quantitative performance and energy models