In this sponsored post on behalf of Intel, we see that in today’s high-performance computing applications, many different pieces of hardware can perform data-centric functions. With diverse accelerators entering the market, programming for multiple architectures has created significant development barriers for software developers.
Paradigm Change: Reinventing HPC Architectures with In-Package Optical I/O
In this white paper, our friends over at Ayar Labs discuss an important paradigm change: reinventing HPC architectures with in-package optical I/O. The introduction of in-package optical I/O technology helps HPC centers accelerate the slope of compute progress needed to tackle ever-growing scientific problem sizes and HPC/AI convergence. Ayar Labs expects to not only see its technology extend the traditional type of architecture to put the HPC industry back on track, but also result in an inflection point that fundamentally changes the slope of the compute performance efficiency curve. The key will be enabling converged HPC/AI centers to build systems with disaggregated CPUs, GPUs, FPGAs and custom ASICs interconnected on equal footing.
Inspur Introduces Leading Designs of NVIDIA A100 Tensor Core GPU Servers for AI and HPC
July 9, 2020 by
In this special guest feature, our friends over at Inspur write about how the company is delivering new servers that address the most demanding performance from companies that are implementing AI and ML into their workflows. Reducing the Total Cost of Ownership (TCO) while increasing the productivity of their teams is critical for CIOs and Line of Business leadership.
Interview: Mark Papermaster, CTO and EVP, Technology and Engineering, AMD
June 3, 2020 by
In this interview, Mark Papermaster, CTO and EVP, Technology and Engineering from AMD describes the company’s presence in the HPC space along with new trends in the industry. At a higher level, Mark also offers his views of the semiconductor industry in general as well as areas of innovation that AMD plans to cultivate. The discussion then turns to the exascale era of computing.
From Forty Days to Sixty-five Minutes without Blowing Your Budget Thanks to Gigaio Fabrex
May 28, 2020 by
In this sponsored post, Alan Benjamin, President and CEO of GigaIO, discusses how the ability to attach a group of resources to one server, run the job(s), and reallocate the same resources to other servers is the obvious solution to a growing problem: the incredible rate of change of AI and HPC applications is accelerating, triggering the need for ever faster GPUs and FPGAs to take advantage of the new software updates and new applications being developed.
Fast Track your AI Workflows
March 26, 2020 by
In this special guest feature, our friends over at Inspur write that for new workloads that are highly compute intensive, accelerators are often required. Accelerators can speed up the computation and allow for AI and ML algorithms to be used in real time. Inspur is a leading supplier of solutions for HPC and AI/ML workloads.
2nd Generation Intel® Xeon® Scalable Processors Demonstrate Amazing HPC Performance
December 5, 2019 by
In this guest article, our friends at Intel discuss how benchmarks show key workloads average 31% better on Intel Xeon Platinum 9282 than AMD EYPC “Rome” 7742. Intel analysis provides strong evidence that the 2nd Generation Intel Xeon Scalable Processor (Cascade Lake “CLX”) architecture provides dramatic performance for real-world workloads. An impressive array of benchmarks shows 2S systems built with Intel’s 56 core processors (Intel Xeon Platinum 9282 processor) solidly ahead of systems built with AMD’s 64 core processors (AMD EYPC 7742).
Optimizing in a Heterogeneous World is (Algorithms x Devices)
November 11, 2019 by
In this guest article, our friends at Intel discuss how CPUs prove better for some important Deep Learning. Here’s why, and keep your GPUs handy! Heterogeneous computing ushers in a world where we must consider permutations of algorithms and devices to find the best platform solution. No single device will win all the time, so we need to constantly assess our choices and assumptions.
