AMD has announced that it is enabling its accelerated processing units (APU) for next-generation servers through important advancements in software tools developed by AMD and in collaboration with technology partners and the open source community.
In his keynote address at APU13, AMD Corporate Fellow Phil Rogers highlighted the significant progress AMD has made in both developing software internally and empowering others to develop software to take advantage of the capabilities of AMD APU technology, which combines industry leading AMD Radeon?s graphics processing engines with x86 computational processing on a single chip.
With the realization that server APUs based on Heterogeneous System Architecture (HSA) are coming to market soon, AMD has developed tools for software developers to take advantage of the benefits that HSA provides. HSA enables the CPU and GPU to work in harmony on a single piece of silicon, seamlessly moving the right tasks to the best-suited processing element with no data transfer penalties and makes more memory available to the GPU so that complex processing tasks can fit in a single node.
AMD is collaborating with its technology partners and the open source community to provide developers with tools that enable them to build server applications that utilise both CPU and GPU compute capabilities available in its revolutionary HSA based server APUs. Tools highlighted today at APU13 include:
Project Sumatra: a joint Oracle and AMD project done in open source that enables developers to code in Java and take advantage of GPU compute;
GCC/HSA Project: an AMD and SUSE project to enable the popular open source Linux compiler, GCC, to support HSA, targeting OpenMP APIs;
PGI Accelerator? Compiler: A beta version is available that enables developers to add OpenACC directives that support AMD APUs and discrete GPUs to Windows and Linux Fortran, C and C++ programs;
clMath: AMD OpenCL math libraries that were contributed to open source in August enable developers to accelerate common scientific and engineering computations on AMD APUs and discrete GPUs;
ArrayFire 2.0 for OpenCL: A fast math library by AccelerEyes that utilises clMath for GPU computing and offers an easy-to-use API for Windows or Linux developers;
CodeXL 1.3: AMD?s coomprehensive developer tool suite for Windows and Linux that features remote debugging and profiling to enable server application developers.
