Case Study: Bosch accelerates deep learning model performance with Embedl SDK

Bosch cuts model latency in half with Embedl

Bosch, a global leader in technology and engineering, faced the challenge of optimizing its proprietary deep learning model for multiple AI accelerator hardware platforms to improve inference speed and efficiency without compromising accuracy or exposing its proprietary data. To meet this goal, they partnered with Embedl and utilized its Model Optimization SDK.

Using Embedl's SDK, Bosch engineers independently executed the optimization, leveraging its advanced techniques like hardware-aware pruning and mixed precision quantization. The solution delivered remarkable results, cutting model latency in half within one week for the initial hardware target and successfully recreating those performance gains when re-optimized for a second platform. This provided Bosch with significant speed improvements for real-time applications and the flexibility to make strategic hardware deployment decisions, all while maintaining model accuracy and data security.

Bosch