LONDON — Achronix is back in the game of providing full-fledged FPGAs with a new high-end 7-nm family, joining the Gold Rush of silicon to accelerate deep learning. It aims to leverage novel design of its AI block, a new on-chip network, and use of GDDR6 memory to provide similar performance at a lower cost than larger rivals Intel and Xilinx.

Achronix debuted in 2004 with an asynchronous design, one of a handful of ambitious FPGA startups at the time. Today, it is the sole survivor thanks to several generations of clever designs and nimble shifts, such as a recent turn to selling embedded FPGA blocks rather than full chips.

The Speedster7t marks the company's return to FPGA chips, targeting the hot market for AI acceleration. Achronix claims that its mid-range 1500 chip can use ResNet-50 and Yolov2 neural-network models to process 8,600 and 1,600 images/second, respectively.

Like its many rivals, the company aims for users such as hyperscale data centers and large networking and storage OEMs. It will start to ship chips and PCIe Gen 5 accelerator boards before the end of the year.

By the time the first hardware ships, it hopes to have software ready to program it directly from TensorFlow. If it has resources and user demand, it will work on support for some of the many other AI frameworks as well as the P4 language. For traditional FPGA users, it will offer its existing RTL programming tools.

“It appears they have a lead customer who has signed up for FPGAs, otherwise they wouldn’t go down this path,” said Bob Wheeler, a senior analyst with the Linley Group. “I believe they had one large lead customer for their past product and likely got them to sign up for the next one.”

The Speedster7t line includes four chips using from 363,000 to 2.6 million six-input lookup tables as well as a number of hardened blocks for high-speed interfaces, including 400 Gigabit Ethernet. That puts it on par with the competition. However, the 150-person company, with annual revenues of about $100 million, competes with rivals Intel and Xilinx that rake in $2 billion to $3 billion a year in FPGAs.

Xilinx is preparing to ship its Versal, a 7-nm family also sporting AI accelerator blocks as well as Arm cores and more. For its part, Intel recently disclosed that its 10-nm Agilex will ship next year, supporting its proprietary EMIB links for standard and custom chiplets. Microsoft already uses existing Intel FPGAs as accelerators on its data center servers.

With constrained resources, Achronix will not attempt to compete with either company for chips with cache-coherent links to a processor. Xilinx helped launch the CCIX interface in 2016, and in March, Intel launched a competing initiative for the CLX link.

The moves create ecosystems that Achronix cannot rival. However, “coherency hasn’t been a big part of the market, and it’s an open question if it ever will be,” said Wheeler. “My take is it will not be big for inference jobs where these parts will be used, but it will be more for training where Nvidia dominates.”