Akamai Introduces Cloud-Based VPUs for Enhanced Video Processing
Akamai has launched Akamai Cloud Accelerated Compute Instances, a new category of cloud-based compute powered by NETINT's video processing units (VPUs), announced in a press release. This makes Akamai the first cloud provider to offer VPUs, which are specialized chips designed to efficiently handle video processing tasks.
The new instances utilize NETINT's Quadra T1U VPUs, capable of encoding up to 32 live streams at 1080p30 broadcast quality. These VPUs are optimized for high-quality video streaming and energy efficiency, supporting resolutions up to 8Kp60 in formats like AV1, HEVC, and H.264. This innovation allows media companies to scale their video delivery services without significant increases in IT costs.
By offloading compute-intensive video tasks to VPUs, companies can free up CPU resources for other applications, enhancing overall system performance. NETINT claims that their VPU architecture offers up to 20 times greater throughput than traditional CPU-only solutions, significantly reducing operational expenses for video streaming services.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Silicon Brief or Daily AI Brief.
Also, consider following us on social media:
More from Data Centers
Nov 14 Telus pulls out of two Vancouver AI data centre projects with Westbank Nov 14 Petition to reinstate Jensen Huang as Nvidia CEO passes 115,000 signatures, with Elon Musk among signers Nov 14 Asian governments respond to Jensen Huang's exit from Nvidia Nov 14 Malaysia plans law making data centres disclose AI chip imports and power use to curb smuggling Nov 14 More than 13,000 object to Chapelcross plan for world's largest AI data centre campusSilicon Brief
Weekly coverage of AI hardware developments including chips, GPUs, cloud platforms, and data center technology.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
Q.ANT and IONOS open a pilot for running AI models on photonic processors in a German cloud
Applied Compute raises $350 million at $3.25 billion valuation
Vū Technologies adds AI meeting capture and new intelligent displays to its visual platform
Nebius Publishes Live Spot Prices for GPU Compute
General Compute Raises $100 Million for Non-Nvidia Inference Cloud
Daily AI Brief: the AI news that matters, in your inbox.