On 16th November 2016, AMD announced a suite of tools designed to ease development of high-performance, energy efficient heterogeneous computing systems. The “Boltzmann Initiative” leverages HSA’s ability to harness both central processing units (CPU) and AMD FirePro graphics processing units (GPU) for maximum compute efficiency through software.
The first results of this initiative are featured this week at SC15 and include the Heterogeneous Compute Compiler (HCC); a headless Linux driver and HSA runtime infrastructure for cluster-class, High Performance Computing (HPC); and the Heterogeneous-compute Interface for Portability (HIP) tool for porting CUDA-based applications to a common C++ programming model. The tools are designed to drive application performance across markets ranging from machine learning to molecular dynamics, and from oil and gas to visual effects and computer-generated imaging.
New Compiler for Heterogeneous Computing
The promise of combining multi-core, serial processing CPUs with parallel-processing GPUs to maximize compute efficiency is already being seen in the industry, as driven by the Heterogeneous Systems Architecture (HSA) Foundation that counts AMD as a founding member. One of the goals for HSA is easing the development of parallel applications through use of higher level languages. The new AMD “Boltzmann Initiative” suite includes an HCC compiler for C++ development, greatly expanding the field of programmers who can leverage HSA. The new HCC C++ compiler is a key tool in enabling developers to easily and efficiently apply the hardware resources in heterogeneous systems. The compiler offers more simplified development via single source execution, with both the CPU and GPU code in the same file. The compiler automates the placement code that executes on both processing elements for maximum execution efficiency.
Linux Driver and Runtime Focused on the Needs of HPC Cluster-Class Computing
To complement the new compilation tools, AMD has developed a new HPC-focused driver and system runtime. This new headless Linux driver brings key capabilities to address core high-performance computing needs, including low latency compute dispatch and PCIe data transfers; peer-to-peer GPU support; Remote Direct Memory Access (RDMA) from InfiniBand that interconnects directly to GPU memory; and Large Single Memory Allocation support.
HIP-ifying CUDA Application to Run on AMD Firepro GPUs
To bring applications written for CUDA onto AMD Firepro platforms, AMD announces the new HIP tool. AMD testing shows that in many cases 90 percent or more of CUDA code can be automatically converted into C++ by HIP with the final 10 percent converted manually in the widely popular C++ language. This greatly expands the installed hardware base available to run what were formerly exclusively CUDA-based applications. At SC15, AMD is demonstrating the potential for HIP, running the CUDA-generated Rodinia benchmark suite on AMD GPUs.
So, AMD is making this Boltzmann initiative tools available in Q1 of 2016. AMD Firepro Developers have now access to use CUDA based applications on AMD platforms. In future, we are going to witness the cross platform applications running on both AMD and Nvidia. AMD Firepro graphic card can run CUDA based applications.