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New Generation of Heterogeneous Systems for AI Applications
JAN 10, 2019 16:51 PM
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New Generation of Heterogeneous Systems for AI Applications

Today’s AI applications will touch every aspect of our lives—including transport, finance, retail, health care, smart manufacturing, education, and services industries. AI technologies will be at the forefront of digitally connected cars, smart manufacturing, and medical image recognition. The question to ask ourselves is how can we leverage the power of AI with today’s diverse systems and protocols? The answer lies in an emerging new ecosystem designed to unite many of today’s heterogeneous “pieces of computing power.”
 
Bringing Abstraction to Heterogeneous Platforms
 
Because heterogeneous processors are widely available, new platforms will be expected to leverage a huge amount of computing power. This includes acceleration units (GPU, DSP, and FPGA).  Understandably, AI/ML/NN are at the forefront of this new computing paradigm. New architectures are also needed to address the massive computing capability augmented by CPU cluster-based computers. Migrating this approach to the mainstream presents a challenge, principally because heterogeneous programming models have not been standardized, lacking portability.  
 
Enter HSA’s Open Computing Platform
 
The challenge facing many industries is that existing architectures are inadequate for today’s AI and big data workloads. An open computing platform of Heterogeneous Systems Architecture (HSA) offers an elegantly viable solution. This new breed of architecture will spearhead an entirely new realm of opportunities, not the least of which are autonomous driving, more computing power, and robust data centers. Systems designers will finally have an efficient new ecosystem, one designed specifically to address today’s burgeoning array of computer architectures and protocols. 
 
Easier Programming of Hetero Devices
 
The HSA Foundation’s consortium of semiconductor companies, tools/IP providers, software vendors, and academic institutions develops royalty-free standards and open-source software. This makes it dramatically easier to program heterogeneous computing devices. It reduces the complexities of heterogeneous systems through a new ecosystem; one that specifies parameters like runtime and system architecture APIs that piggyback cache-coherent shared virtual memory hardware. No more time-consuming operating system calls. Systems now run at the user level. With single-source programming, both control and computer code reside in the same file or project. No need for expert programmers to decipher tool-chains of multiple processors for individual access. 
 
Programming in Standard Languages
 
Another key benefit for AI applications developers is that the HSA platform conforms to a variety of different programming languages. Compilation tools are available from both proprietary and open-source projects (LLVM and GCC). HSA compilers are available for C/C++, OpenCL, OpenMP, C++AMP, Python and more. This flexibility vastly extends the power and reach of AI applications now on many drawing boards. 
 
Leveraging Developer Productivity
 
Defined as a productivity engine that leverages the power and potential of heterogeneous computing, HSA removes many of the barriers of traditional heterogeneous programming. Developers can finally focus on their algorithms without having to micro-manage system resources. The goal is to sponsor applications that seamlessly blend scalar processing with high-performance computing on CPU’s, GPU’s, DSP’s, Image Signal Processors, VLIW’s, Neural Network Processors, FPGA’s, and more.
 
There’s little doubt that AI applications will impact how we live work and play. AI technologies will be at the forefront of digitally connected transportation, smart manufacturing, and medical technologies. But it will be the power and flexibility of  heterogeneous computing that will make these AI breakthroughs feasible and change the face of our world. 
 
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