Documentation

AI requires a careful balance of datapath performance, memory latency, and throughput that requires an approach based on pulling as much of the functionality as possible into an ASIC or SoC. But that single-chip device needs plasticity to be able to handle the changes in structure that are inevitable in machine-learning projects. Adding eFPGA technology provides the mixture of flexibility and support for custom logic that the market requires. Achronix provides not only the building blocks required for an AI-ready eFPGA solution, but also delivers a framework that supports design through to debug and test of the final application. Only Achronix Speedcore IP has the right mix of features for advanced AI that will support a new generation of real-time, self-learning systems.

Phase zero is the beginning of a Speedcore design and how you begin matters. From a technical perspective, you will want to explore the possibilities to maximize the benefit of having your ASIC deployed with a Speedcore instance with a mix of resources well suited to your current and future programmed configurations. Achronix will help you along this road, providing support, training and feedback in employing tools, benchmarking designs and dealing with optimization issues.

The Speedcore design and integration methodology has been defined with intimate awareness of the difficulties ASIC engineering teams must contend with. All the necessary files and flows for capturing the functional, timing and power characteristics of a user-defined and programmed Speedcore instance, along with support for successfully reconfiguring an already field-deployed Speedcore IP embedded in an ASIC, are available to an ASIC development team either as products of the ACE design tools or as deliverables provided by Achronix. This methodology has already been proven in silicon and readily accommodates variations and preferences in company-specific ASIC development methodologies.

The current public debate on the future of the semiconductor industry has turned to discussions about a growing selection of technologies that focuses instead on new system architectures and better use of available silicon through new concepts in circuit, device, and packaging design. The emergence of embedded FPGA is, in fact, not only essential at this juncture of the microelectronics history, but also inevitable. To understand this, a review of the history of FPGA technology is in order.

With the technology industry at a crossroads — the effective repeal of Moore's Law  — data centers have become the sweet spot of the technology sector, showing healthy revenue growth and attracting new system solutions in both hardware and software. Unlike the ethereal promise of upcoming wonders from AI, robotics and the IoT, data center growth and innovation is happening in the here and now, with an even brighter future ahead the moment other nascent markets emerge from their chrysalis with killer apps of their own.