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Vendor:
Tenstorrent
Category:
NPU
Future-proof IP for training and inference with leading performance per watt and per dollar
Tenstorrent develops AI IP with precision, anchored in RISC-V’s open architecture, delivering specialized, silicon-proven solutio…
Overview
Tenstorrent develops AI IP with precision, anchored in RISC-V’s open architecture, delivering specialized, silicon-proven solutions for both AI training and inference. Our platforms are optimized for high performance per watt, ensuring scalable and adaptable technology for all AI-specific workloads.
Tensix Cores allow AI developers to accelerate their specific AI networks and applications in an efficient and easy-to-use manner. Our platforms are optimized for high performance-per-watt, ensuring adaptable technology for all AI-specific workloads. Tensix Cores support a broad range of precision formats and connect using a specially designed Network-on-Chip (NoC), allowing your solution to scale in concert with an ever-expanding list of models and evolve with the industry. Tensix is silicon-proven with two generations of products - Grayskull™ and Wormhole™ - and a third generation in active development. Each Tensix Core incorporates a block of SRAM, five “baby RISC-V” cores, Matrix and Vector Engines, and dedicated hardware streams built upon ethernet protocols that facilitate rapid core-to-core and chip-to-chip communication.
Key features
- RISC-V IP Optimized for AI
- Designed specifically for advanced AI/ML workloads.
- Silicone-Tested
- Solutions have been validated on silicon for AI workload efficiency.
- Adaptable Technology
- AI technology platforms that are scalable and customizable.
- Quick to Market
- AI IP that enables swift and flexible integration for rapid deployment.
- Power-Efficient
- Delivers top-tier performance with minimal power consumption.
Block Diagram
Tensix Neo block diagram
Benefits
- MMUL ops/cycle: 4096
- SIMD ops/cycle: 64
- Data types: INT, FP, BFP
- SRAM: 1.5MB
Applications
- Automotive AI, Data Centers, HPC, Wearables, Smart Cameras, DTV, and More. Accelerating CNNs, LLMs, Transformers, and other AI workloads with high efficiency and utilization.
Files
Note: some files may require an NDA depending on provider policy.
Specifications
Identity
Part Number
Tensix Neo
Vendor
Tenstorrent
Provider
Tenstorrent
HQ:
Canada
Tenstorrent is a next-generation computing company that builds computers for AI. Headquartered in Toronto, Canada, with U.S. offices in Austin, Texas, and Silicon Valley, and global offices in Belgrade, Tokyo, and Bangalore, Tenstorrent brings together experts in the field of computer architecture, ASIC design, advanced systems, and neural network compilers. Tenstorrent is backed by Fidelity, Hyundai Motor Group, Samsung, Eclipse Ventures and Real Ventures, among others.
Learn more about NPU IP core
Heterogeneous NPU Data Movement Tax: Intel's Own Slides Tell the Story
At Quadric, we have long argued that heterogeneous NPU designs — those that stitch together multiple specialized fixed-function engines — carry an unavoidable hidden cost: data has to move. A lot. And data movement burns power, adds latency, and creates silicon-area overhead that scales with every new generation of AI models. Now, Intel has made that case for us.
The Upcoming NPU Shakeout
The IP industry is no stranger to boom and bust cycles, and it looks to be at the crest of another wave.
One Instruction Stream, Infinite Possibilities: The Cervell™ Approach to Reinventing the NPU
AI is evolving faster than the chips designed to run it. Models like large language transformers and generative networks are shifting rapidly–while silicon development cycles remain long and rigid. Traditional NPUs, built around proprietary instruction sets and opaque compilers, simply can’t keep up.
Legacy IP Providers Struggle to Solve the NPU Dilemna
Just bolting a matrix accelerator onto existing processor IP leads to long-term challenges.
Can You Rely Upon your NPU Vendor to be Your Customers' Data Science Team?
Frequently asked questions about NPU IP cores
What is Future-proof IP for training and inference with leading performance per watt and per dollar?
Future-proof IP for training and inference with leading performance per watt and per dollar is a NPU IP core from Tenstorrent listed on Semi IP Hub.
How should engineers evaluate this NPU?
Engineers should review the overview, key features, supported foundries and nodes, maturity, deliverables, and provider information before shortlisting this NPU IP.
Can this semiconductor IP be compared with similar products?
Yes. Buyers can compare this product with similar semiconductor IP cores or IP families based on category, provider, process options, and structured technical specifications.