Today AMD unveiled preliminary details of its forthcoming GPU architecture, Vega. Conceived and executed over 5 years, Vega architecture enables new possibilities in PC gaming, professional design and machine intelligence that traditional GPU architectures have not been able to address effectively. “It is incredible to see GPUs being used to solve gigabyte-scale data problems in gaming to exabyte-scale data problems in machine intelligence. We designed the Vega architecture to build on this ability, with the flexibility to address the extraordinary breadth of problems GPUs will be solving not only today but also five years from now. Our high-bandwidth cache is a pivotal disruption that has the potential to impact the whole GPU market,” said Raja Koduri, senior vice president and chief architect, Radeon Technologies Group, AMD.
“New Radeon Instinct accelerators will offer organizations powerful GPU-based solutions for deep learning inference and training. Along with the new hardware offerings, AMD announced MIOpen, a free, open-source library for GPU accelerators intended to enable high-performance machine intelligence implementations, and new, optimized deep learning frameworks on AMD’s ROCm software to build the foundation of the next evolution of machine intelligence workloads.”
In this video from SC16, Ben Sander from AMD presents: HIP and CAFFE Porting and Profiling with AMD’s ROCm. “We are excited to present ROCm, the first open-source HPC/Hyperscale-class platform for GPU computing that’s also programming-language independent. We are bringing the UNIX philosophy of choice, minimalism and modular software development to GPU computing. The new ROCm foundation lets you choose or even develop tools and a language run time for your application. ROCm is built for scale; it supports multi-GPU computing in and out of server-node communication through RDMA.”
In this podcast, the Radio Free HPC team looks at the new OpenCAPI interconnect standard. “Released this week by the newly formed OpenCAPI Consortium, OpenCAPI provides an open, high-speed pathway for different types of technology – advanced memory, accelerators, networking and storage – to more tightly integrate their functions within servers. This data-centric approach to server design, which puts the compute power closer to the data, removes inefficiencies in traditional system architectures to help eliminate system bottlenecks and can significantly improve server performance.”
Today AMD announced that the Alibaba Cloud will use AMD Radeon Pro GPU technology to help expand its cloud computing offerings and accelerate adoption of its cloud-based services. “The partnership between AMD and Alibaba Cloud will bring both of our customers more diversified, cloud-based graphic processing solutions. It is our vision to work together with leading technology firms like AMD to empower businesses in every industry with cutting-edge technologies and computing capabilities,” said Simon Hu, president of Alibaba Cloud.
“IBM has decided to double down on our commitment to open standards and enablement of industry innovation by opening up access to our CAPI technology to the entire industry. With the support of our OpenCAPI co-founders, we have created a new OpenCAPI specification that tremendously improves performance over our prior specification and IBM will be among the first to implement it with our POWER9 products expected in 2017.”
In this video from the 2016 HPC User Forum in Austin, a select panel of HPC vendors describe their disruptive technologies for high performance computing. Vendors include: Altair, SUSE, ARM, AMD, Ryft, Red Hat, Cray, and Hewlett Packard Enterprise. “A disruptive innovation is an innovation that creates a new market and value network and eventually disrupts an existing market and value network, displacing established market leading firms, products and alliances.”
“AMD has been away from the HPC space for a while, but now they are coming back in a big way with an open software approach to GPU computing. The Radeon Open Compute Platform (ROCm) was born from the Boltzmann Initiative announced last year at SC15. Now available on GitHub, the ROCm Platform bringing a rich foundation to advanced computing by better integrating the CPU and GPU to solve real-world problems.”
The Central Processing Unit (CPU) has been at the heart of High Performance Computing (HPC) for decades. However, in recent years, advances in parallel processing technology mean the landscape has changed dramatically. To learn more download this white paper.
AMD’s motivation for developing these open-source GPU tools is based on an opportunity to remove the added complexity of proprietary programming frameworks to GPU application development. “If successful, these tools – or similar versions – could help to democratize GPU application development, removing the need for proprietary frameworks, which then makes the HPC accelerator market much more competitive for smaller players. For example, HPC users could potentially use these tools to convert CUDA code into C++ and then run it on an Intel Xeon co-processor.”