Arteris Network-on-Chip Tiling Innovation Accelerates Semiconductor Designs for AI Applications
15 Octubre 2024 - 8:00AM
Arteris, Inc. (Nasdaq: AIP), a leading provider of system IP which
accelerates system-on-chip (SoC) creation, today announced an
innovative evolution of its network-on-chip (NoC) IP products with
tiling capabilities and extended mesh topology support for faster
development of Artificial Intelligence (AI) and Machine Learning
(ML) compute in system-on-chip (SoC) designs. The new functionality
enables design teams to scale compute performance by more than 10
times while meeting project schedules plus power, performance and
area (PPA) goals.
Network-on-chip tiling is an emerging trend in SoC design. The
evolutionary approach uses proven, robust network-on-chip IP to
facilitate scaling, condense design time, speed testing and reduce
design risk. It allows SoC architects to create modular, scalable
designs by replicating soft tiles across the chip. Each soft tile
represents a self-contained functional unit, enabling faster
integration, verification and optimization.
Tiling coupled with mesh topologies within Arteris’ flagship NoC
IP products, FlexNoC and Ncore, are transformative for the
ever-growing inclusion of AI compute into most SoCs. AI-enabled
systems are growing in size and complexity yet can be quickly
scaled with the addition of soft tiles without disrupting the
entire SoC design. Together, the combination of tiling and mesh
topologies provides a way to further reduce the auxiliary
processing unit (XPU) sub-system design time and overall SoC
connectivity execution time by up to 50% versus manually
integrated, non-tiled designs.
The first iteration of NoC tiling organizes Network Interface
Units (NIUs) into modular, repeatable blocks, improving
scalability, efficiency and reliability in SoC designs. These SoC
designs result in increasingly larger and more advanced AI compute
which supports fast-growing, sophisticated AI workloads for Vision,
Machine Learning (ML) models, Deep Learning (DL), Natural Language
Processing (NLP) including Large Language Models (LLMs), and
Generative AI (GAI), both for training and inference, including at
the edge.
“Thanks to Arteris’ highly scalable and flexible mesh-based NoC
IP, our SoC team has implemented support for larger AI data volumes
and complex algorithms more efficiently. The close collaboration
with Arteris has enabled us to create an Arm-based, multi-modal,
software-centric edge AI platform that supports models ranging from
CNNs to multimodal GenAI and everything in between with scalable
performance per watt,” said Srivi Dhruvanarayan, VP of hardware
engineering at SiMa.ai. “We look forward to deploying the expanded
Arteris NoC tiling and mesh functionality, which should further
enhance our ability to create highly scalable AI silicon platforms
for the edge.”
“Arteris is continuously innovating, and this revolutionary NoC
soft tiling functionality supported by large mesh topologies is an
advancement in SoC design technology,” said K. Charles Janac,
president and CEO of Arteris. “Our customers, who are already
building leading-edge AI-powered SoCs, are further empowered to
accelerate the development of much larger and more complex AI
systems with greater efficiency, all while staying within their
project timeline and PPA targets.”
The FlexNoC and Ncore NoC IP products, which offer expanded AI
support via tiling and extended mesh topology capabilities, are now
available to early-access customers and partners. To learn more,
visit arteris.ai.
About Arteris
Arteris is a leading provider of system IP for the acceleration
of system-on-chip (SoC) development across today's electronic
systems. Arteris network-on-chip (NoC) interconnect IP and SoC
integration automation technology enable higher product performance
with lower power consumption and faster time to market, delivering
better SoC economics so its customers can focus on dreaming up what
comes next. Learn more at arteris.com.
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Media Contact:Gina JacobsArteris+1 408 560
3044newsroom@arteris.com
This press release was published by a CLEAR® Verified
individual.
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