Accelerator provides easy deployment for deep learning models

Mouser now stocks the GroqCard Accelerator from BittWare. This double-width PCIe form factor ML accelerator provides easy deployment paths for PyTorch, TensorFlow, and ONNX-trained deep learning models. The device is versatile for accelerating AI, HPC, and ML workloads for financial, government, generative AI, energy, and industrial applications.

The device features nine RealScale chip-to-chip connections to ensure multiple cards can be deployed as efficiently as one. The accelerator provides near-linear, multi-server, and multi-rack scalability without external switches. ECC protects against data corruption for improved uptime and reliability. The device features the fully deterministic GroqChip processor for improved scalability. By lowering data movement, the GroqChip ensures predictable, bottleneck-free, low-latency performance. The standalone chip provides for flexible integration into compute-intensive applications, while its simplified architecture and software-first focus make the GroqChip processor easier to program than a GPU.

The GroqWare Suite, a comprehensive and versatile software stack, is composed of the Groq Compiler, Groq API, and utilities. The suite simplifies the integration and setup process and is compatible with industry-standard AI and ML frameworks. The GroqFlow Tool Chain, included in the GroqWare Suite, allows a single line of Pytorch or TensorFlow code to import and transform existing models. The device offers up to 750 TOPs and 188 TFLOPs at a frequency of 900MHz for INT8 and FP16 operations. The GroqCard Accelerator features 230MB of SRAM per chip and up to 80TB/s on-die memory bandwidth to allow high-speed data access and processing.