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BittWare GroqCard™ Accelerator is a double-width PCIe form factor ML accelerator developed to integrate easily. The GroqWare™ suite implements a software-defined hardware approach, allowing easy deployment paths for PyTorch, TensorFlow, and ONNX-trained deep learning models. The BittWare GroqCard Accelerator features scalability with nine RealScale™ chip-to-chip connections that guarantee the deployment of multiple cards as efficiently as one. Furthermore, an internal software-defined network delivers predictable, repeatable performance with no run-to-run variations. The GroqCard has been qualified for use with the SMC AS-4124GS-TNR and Dell R750xa. The HPE DL385 Gen 10 Plus has been tested, but the full server interop exercise was not completed. In addition, liquid has also qualified the GroqCard in the chassis with up to 16 GroqCards. Using the GroqCard in other server models is at the user’s risk.
The fully deterministic GroqChip processor is the core of scalable performance. Built from the ground up to accelerate AI, ML, and HPC workloads, GroqChip reduces data movement for predictable low-latency performance, bottleneck-free. This standalone chip provides flexible integration into compute-intensive applications. The architecture is much simpler than a GPU and is designed with a software-first focus, making it easier to program and providing predictable performance with lower latency.
GroqWare Suite is a comprehensive and versatile software stack designed to accelerate a variety of HPC and ML workloads. Composed of Groq™ Compiler, Groq API, and Utilities, the suite eases deployment implementations with an open-source driver/runtime and support for industry-standard AI/ML frameworks. GroqFlow™ Tool Chain (included in the GroqWare Suite) enables a single line of Pytorch or TensorFlow code to import and transform existing models through a fully automated toolchain to run on Groq hardware.
