Deci delivers breakthrough inference performance on Intel’s 4th Gen Sapphire Rapids CPU

Deci, the deep learning company building the next generation of AI, announced a breakthrough performance on Intel’s newly released 4th Gen Intel® Xeon® Scalable processors, code-named Sapphire Rapids. By optimizing the AI models which run on Intel’s new hardware, Deci enables AI developers to achieve GPU-like inference performance on CPUs in production for both Computer Vision and Natural Language Processing (NLP) tasks.

The Looming Datacenter Paradigm Shift

In this contributed article, Jonathan Friedmann, CEO & Co-Founder of Speedata, discusses a paradigm shift that is already underway. CPU’s leading role in datacenters is no longer a given, and as database workloads grow increasingly varied, market forces will point more and more in a clear direction: the development of new, dedicated, accelerated solutions. Data workloads are only going to grow more diverse and intricate from here. The same holds true for the chips that will process them.

Deeplite Accelerates AI on Arm CPUs Using Ultra-Compact Quantization

Deeplite, a provider of AI optimization software designed to make AI model inference faster, more compact and energy-efficient, today announced Deeplite Runtime (DeepliteRT), a new addition to its platform that makes AI models even smaller and faster in production deployment, without compromising accuracy. Customers will benefit from lower power consumption, reduced costs and the ability to utilize existing Arm CPUs to run AI models.

Deci and Intel Collaborate to Optimize Deep Learning Inference on Intel’s CPUs

Deci, the deep learning company building the next generation of AI, announced a broad strategic business and technology collaboration with Intel Corporation to optimize deep learning inference on Intel Architecture (IA) CPUs. As one of the first companies to participate in Intel Ignite startup accelerator, Deci will now work with Intel to deploy innovative AI technologies to mutual customers.

Interview: Global Technology Leader PNY

The following whitepaper download is a reprint of the recent interview with our friends over at PNY to discuss a variety of topics affecting data scientists conducting work on big data problem domains including how “Big Data” is becoming increasingly accessible with big clusters with disk-based databases, small clusters with in-memory data, single systems with in-CPU-memory data, and single systems with in-GPU-memory data. Answering our inquiries were: Bojan Tunguz, Senior System Software Engineer, NVIDIA and Carl Flygare, NVIDIA Quadro Product Marketing Manager, PNY.

Interview: Global Technology Leader PNY

We recently caught up with our friends over at PNY to discuss a variety of topics affecting data scientists conducting work on big data problem domains including how “Big Data” is becoming increasingly accessible with big clusters with disk-based databases, small clusters with in-memory data, single systems with in-CPU-memory data, and single systems with in-GPU-memory data. Answering our inquiries were: Bojan Tunguz, Senior System Software Engineer, NVIDIA and Carl Flygare, NVIDIA Quadro Product Marketing Manager, PNY.