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PathScale® ENZO is a complete GPGPU and multi-core solution, which tightly couples the best programming models with highly optimizing code generation for NVIDIA Tesla. ENZO reflects our dedication to and investment in GPGPU with over a decade of combined engineering time invested so far. By leveraging the HMPP open standard directives, ENZO does optimizations that quickly transform any existing C, C++ or Fortran codebase into highly efficient parallel code for GPU or multi-core systems.
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• Optimized for NVIDIA Tesla
• HMPP C, C++ and Fortran
• GPGPU & multi-core combined
• CUDA support and powerful tools
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Strengths of HMPP
HMPP directives are well tuned for GPGPU and the result of two years feedback from production use by CAPS' customers. In 2010 it was made an open standard, to be jointly developed by CAPS and PathScale, each creating independent implementations and removing the risk of single vendor lock in. Unlike solutions such as OpenCL, HMPP works by annotating existing code. This means that you can quickly add GPGPU support to performance-critical parts of your existing codebase without the need to learn a new language or rewrite portions, potentially introducing new bugs. HMPP is intended to be easy to learn for anyone familiar with OpenMP, but designed with future heterogeneous multicore systems in mind, preserving your investment in your code.
ENZO highlights
• High performance C, C++, and Fortran EKOPath compilers
• HMPP C, C++[1] and Fortran compilers
• PathScale C++ template and class libraries for GPGPU[2]
• CUDA[3] compatible compiler
• PathDB debugger with GPGPU support
• PathAS assembler with GPGPU support
• PSCNV open source compute Tesla driver
• True GPGPU network Zero copy[4]
• Productivity tools for GPGPU programming[5]
• Only GPGPU solution for Linux, Solaris and FreeBSD[6]
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