aiWare™

Hardware IP for Automotive AI

aiWare4+: Enhanced flexibility with class-leading efficiency for the most demanding automotive workloads

aiWare4+ builds on the 4th generation of aiMotive's aiWare NPU hardware IP, enhancing its flexibility and programmability while offering best-in-class efficiency on the widest possible automotive inferencing workloads. Featuring innovative wavefront-processing, ISO26262-compliant aiWare4+ is future-ready to cater to the industry trends in autonomous driving workloads such as Transformer Networks and FP8 format. With new features that improve and power and performance such as support for fine grained structured sparsity and interleaved multitasking aiWare4 delivers the ultimate scalable solution from the most challenging single-chip edge applications to the highest performance central processing platforms for automotive AI.

Flexibility for Next-Gen Worloads

Enhacnements to aiWare HW and SDK upgrades mean higher performance not only for CNNs but a wider range of workloads including LSTMs and emerging workloads such as Transformer Networks to deliver a future-proof for the most demanding workloads.

FP8 Support

Supplementing the INT8 support, aiWare4+ adds the option for FP8 format to take advantage of industry standardization and ecosystem support for FP8 for workloads that can take advantage of this format for better performance and accuracy.

Fine-grained Structured Sparsity

aiWare4+ HW and SW upgrades enable users to take advantage of Fine-grained Structured Sparsity to improve performance and power, building on the growing eco-system support for tools and frameworks.

Improved Multitasking & Scalability

With features such as Interleaved Multitasking, aiWare ensures that multiple workloads can be scheduled concurrently if possible to deliver higher resource utilization to best utilize the available TOPS to enable centralized compute paradigm.

Efficiency

aiWare4+ extends aiMotive’s leadership with up to 98% efficiency over a wider range of NN topologies. This efficiency scales especially for large input sizes such as early fusion of multiple different high data rate sensors, or from one or multiple high resolution camera sensors.
Want to know more about the technical details?

Read aiWare4+'s specification

From key features to memory and Neural Network development frameworks – you can find out what aiWare4+ offers for automotive inference.

See the specification sheet
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