Intel and recently acquired Altera have launched a new FPGA product based on Intel’s 14nm Tri-Gate process featuring an ARM CPU, 5.5 million logic element FPGA, and HBM2 memory in a single package. The Stratix 10 is aimed at data center, networking, and radar/imaging customers.
The Stratix 10 is an Altera-designed FPGA (field programmable gate array) with 5.5 million logic elements and a new HyperFlex architecture that optimizes registers, pipeline, and critical pathing (feed-forward designs) to increase core performance and increase the logic density by five times that of previous products. Further, the upcoming FPGA SoC reportedly can run at twice the core performance of Stratix V or use up to 70% less power than its predecessor at the same performance level.
The increases in logic density, clockspeed, and power efficiency are a combination of the improved architecture and Intel’s 14nm FinFET (Tri-Gate) manufacturing process.
Intel rates the FPGA at 10 TFLOPS of single precision floating point DSP performance and 80 GFLOPS/watt.
Interestingly, Intel is using an ARM processor to feed data to the FPGA chip rather than its own Quark or Atom processors. Specifically, the Stratix 10 uses an ARM CPU with four Cortex A53 cores as well as four stacks of on package HBM2 memory with 1TB/s of bandwidth to feed data to the FPGA. There is also a “secure device manager” to ensure data integrity and security.
The Stratix 10 is aimed at data centers and will be used with in specialized tasks that demand high throughput and low latency. According to Intel, the processor is a good candidate for co-processors to offload and accelerate encryption/decryption, compression/de-compression, or Hadoop tasks. It can also be used to power specialized storage controllers and networking equipment.
Intel has started sampling the new chip to potential customers.
In general, FPGAs are great at highly parallelized workloads and are able to efficiently take huge amounts of inputs and process the data in parallel through custom programmed logic gates. An FPGA is essentially a program in hardware that can be rewired in the field (though depending on the chip it is not necessarily a “fast” process and it can take hours or longer to switch things up heh). These processors are used in medical and imaging devices, high frequency trading hardware, networking equipment, signal intelligence (cell towers, radar, guidance, ect), bitcoin mining (though ASICs stole the show a few years ago), and even password cracking. They can be almost anything you want which gives them an advantage over traditional CPUs and graphics cards though cost and increased coding complexity are prohibitive.
The Stratix 10 stood out as interesting to me because of its claimed 10 TFLOPS of single precision performance which is reportedly the important metric when it comes to training neural networks. In fact, Microsoft recently began deploying FPGAs across its Azure cloud computing platform and plans to build the “world’s fastest AI supercomputer. The Redmond-based company’s Project Catapult saw the company deploy Stratix V FPGAs to nearly all of its Azure datacenters and is using the programmable silicon as part of an “acceleration fabric” in its “configurable cloud” architecture that will be used initially to accelerate the company’s Bing search and AI research efforts and later by independent customers for their own applications.
It is interesting to see Microsoft going with FPGAs especially as efforts to use GPUs for GPGPU and neural network training and inferencing duties have increased so dramatically over the years (with NVIDIA being the one pushing the latter). It may well be a good call on Microsoft’s part as it could enable better performance and researchers would be able to code their AI accelerator platforms down to the gate level to really optimize things. Using higher level languages and cheaper hardware with GPUs does have a lower barrier to entry though. I suppose ti will depend on just how much Microsoft is going to charge customers to use the FPGA-powered instances.
FPGAs are in kind of a weird middle ground and while they are definitely not a new technology, they do continue to get more complex and powerful!
What are your thoughts on Intel's new FPGA SoC?