Achronix Introduces FPGA Family

May 21, 2019

SANTA CLARA, Calif., May 21, 2019 — Achronix Semiconductor Corporation, a leader in FPGA-based hardware accelerator devices and high-performance eFPGA IP, today introduced an innovative, new FPGA family, to meet the growing demands of artificial intelligence/ machine learning (AI/ML) and high-bandwidth data acceleration applications. The Achronix Speedster7t family – based on a new, highly optimized architecture – goes beyond traditional FPGA solutions featuring ASIC-like performance, FPGA adaptability and enhanced functionality to streamline design.

Specifically designed for AI/ML and high-bandwidth workloads, the Speedster7t FPGA family features a revolutionary new 2D network-on-chip (NoC), and a high-density array of new machine learning processors (MLP). Blending FPGA programmability with ASIC routing structures and compute engines, the Speedster7t family creates a new “FPGA+” class of technology.

As use cases for AI/ML are rapidly evolving, new solutions are required to address the varying requirements of high performance, flexibility and time to market. As a result, Semico Research Corp. forecasts the market size for FPGAs in AI applications will grow by 3x in the next four years to $5.2 billion.

“We are at the beginning of a high-growth phase of intelligent, self-learning computation that will have broad impacts on all aspects of our daily lives,” said Robert Blake, President and CEO of Achronix Semiconductor. “The Speedster7t family is the most exciting announcement in the history of Achronix, representing innovation and learning across four architectural generations of hardware and software development and close cooperation with our lead customers. The Speedster7t family is the fusion of flexible FPGA technology with ASIC core efficiency to deliver a new “FPGA+” class of chips that truly push the boundaries of high-performance compute acceleration.”

In developing the Speedster7t family of FPGAs, Achronix’s engineering team redesigned the entire FPGA architecture to balance on-chip processing, interconnect and external I/O, to maximize the throughput of data-intensive workloads such as those found in edge- and server-based AI/ML applications, networking and storage.

Manufactured on TSMC’s 7nm FinFET process, Speedster7t devices are designed to accept massive amounts of data from multiple high-speed sources, distribute that data to programmable on-chip algorithmic and processing units, and then deliver those results with the lowest possible latency. Speedster7t devices include high-bandwidth GDDR6 interfaces, 400G Ethernet ports, and PCI Express Gen5 — all interconnected to deliver ASIC-level bandwidth while retaining the full programmability of FPGAs.

“The new Achronix Speedster7t FPGA family is a prime example of the explosion of innovative silicon architectures created to handle massive amounts of data that are aimed directly at AI applications,” said Rich Wawrzyniak, principal market analyst for ASIC & SoC at Semico Research. “Combining math functions, memory and programmability into their machine learning processor, combined with the cross-chip, two-dimensional NoC structure, is a brilliant method of eliminating bottlenecks and ensuring the free flow of data throughout the device. In AI/ML applications, memory bandwidth is everything and the Achronix Speedster7t family delivers impressive performance metrics in this area.”

Optimized for Compute Performance

At the heart of Speedster7t FPGAs are a massively parallel array of programmable compute elements within the new MLPs that deliver the industry’s highest FPGA-based compute density. The MLPs are highly configurable, compute-intensive blocks that support integer formats from 4 to 24 bits and efficient floating-point modes including direct support for TensorFlow’s 16-bit format as well as the supercharged block floating-point format that doubles the compute engines per MLP.

The MLPs are tightly coupled with embedded memory blocks, eliminating the traditional delays associated with FPGA routing to ensure that data is delivered to the MLPs at the maximum performance of 750 MHz. This combination of high-density compute and high-performance data delivery results in a processor fabric that delivers the highest usable FPGA-based tera-operations per second (TOps).

World-class Bandwidth

Critical for high-performance compute and machine learning systems is high off-chip memory bandwidth to source and buffer multiple data streams. Speedster7t devices are the only FPGAs with support for GDDR6 memories, the highest bandwidth external memory devices. With each of the GDDR6 memory controllers capable of supporting 512 Gbps of bandwidth, the up to 8 GDDR6 controllers in a Speedster7t device can support an aggregate GDDR6 bandwidth of 4 Tbps, delivering the equivalent memory bandwidth of an HBM-based FPGA at a fraction of the cost.

“Micron is pleased to collaborate with Achronix to enable the world’s first FPGA with direct attached GDDR6 for high-bandwidth memory requirements,” said Mal Humphrey, Vice President of Marketing for Micron’s Compute and Networking Business Unit. “Innovative and scalable solutions like these will drive differentiation in areas of AI where heterogeneous compute options, combined with high-performance memory, are needed to accelerate data insights.”

Along with this extraordinary memory bandwidth, Speedster7t devices include the industry’s highest performance interface ports to support extremely high-bandwidth data streams. Speedster7t devices have up to 72 of the industry’s highest performance SerDes that can operate from 1 to 112 Gbps plus hard 400G Ethernet MACs with forward error correction (FEC), supporting 4x 100G and 8x 50G configurations, plus hard PCI Express Gen5 controllers with 8 or 16 lanes per controller.

Super-efficient Data Movement

While the many terabits of data from the Speedster7t high-speed I/O and memory ports would easily overwhelm the routing capacity of a conventional FPGA’s bit-oriented programmable-interconnect fabric, the Speedster7t architecture includes an innovative, high-bandwidth, two-dimensional NoC that spans horizontally and vertically over the FPGA fabric, connecting to all of the FPGA’s high-speed data and memory interfaces. Acting like a superhighway network superimposed on the city street system of the FPGA interconnect, the Speedster7t NoC supports the high-bandwidth communication needed between on-chip processing engines. Each row or column in the NoC is implemented as two 256-bit, unidirectional industry-standard AXI channels operating at a 2 Ghz, delivering 512 Gbps of data traffic in each direction simultaneously.

The implementation of a dedicated 2D NoC greatly simplifies high-speed data movement and ensures that data streams can easily be directed to any of the custom-defined processing engines throughout the FPGA fabric. Most importantly, the NoC eliminates the congestion and performance bottlenecks that occur in traditional FPGAs that use the programmable routing and logic lookup table (LUT) resources to move data streams throughout the FPGA. This high-performance network not only increases the overall bandwidth capacity of Speedster7t FPGAs, but also increases the effective LUT capacity while reducing power.

Security Features for Safety Critical and Hardware Assurance Applications

Speedster7t FPGAs confront the threat of third-party attacks with the most advanced bitstream security features with multiple layers of defense for protecting bitstream secrecy and integrity. Keys are encrypted based on a tamper-resistant physically unclonable function (PUF), and bitstreams are encrypted and authenticated by 256-bit AES-GCM. To defend against side-channel attacks, bitstreams are segmented, with separately derived keys used for each segment, and the decryption hardware employs differential power analysis (DPA) counter measures. Additionally, a 2048-bit RSA public key authentication protocol is used to activate the decryption and authentication hardware. Users can be confident that when they load their secure bitstream, it is the intended configuration because it has been authenticated by RSA public key, AES-GCM private key, and a CRC checksum.

Proven Conversion Path to Low-cost ASIC for High-volume Requirements

Achronix is the only company that offers both standalone FPGAs and Speedcore™ embedded FPGA IP. Speedcore eFPGA IP is the same technology that Achronix uses in its Speedster7t FPGAs, which allows for a seamless conversion from Speedster7t FPGA to ASIC. FPGA applications typically have functions that must remain programmable, while others are fixed functions that are dedicated to the specific system application. For ASIC conversions, the fixed functions can be hardened into the ASIC structure, which reduces die size, cost and power. Customers can expect to get up to 50 percent power reduction and 90 percent cost reduction when they use Speedcore eFPGA IP to convert Speedster7t FPGAs to ASIC.

Availability

The Speedster7t FPGA devices range from 363K to 2.6M 6-input LUTs. The ACE design tools that support all of Achronix’s products including Speedcore eFPGA and Speedchip™ FPGA chiplets are available today.

The first devices and development boards for evaluation will be available in Q4 2019.

About Achronix Semiconductor Corporation

Achronix Semiconductor Corporation is a privately held, fabless semiconductor corporation based in Santa Clara, California and offers high-performance FPGA and embedded FPGA (eFPGA) solutions. Achronix’s history is one of pushing the boundaries in the high-performance FPGA market. Achronix offerings include programmable FPGA fabrics, discrete high-performance and high-density FPGAs with hardwired system-level blocks, datacenter and HPC hardware accelerator boards, and best-in-class EDA software supporting all Achronix products. The company has sales offices and representatives in the United StatesEurope, and China, and has a research and design office in Bangalore, India.


Source: Achronix Semiconductor Corporation

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, code-named Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from its predecessors, including the red-hot H100 and A100 GPUs. Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. While Nvidia may not spring to mind when thinking of the quant Read more…

2024 Winter Classic: Meet the HPE Mentors

March 18, 2024

The latest installment of the 2024 Winter Classic Studio Update Show features our interview with the HPE mentor team who introduced our student teams to the joys (and potential sorrows) of the HPL (LINPACK) and accompany Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the field was normalized for boys in 1969 when the Apollo 11 missi Read more…

Apple Buys DarwinAI Deepening its AI Push According to Report

March 14, 2024

Apple has purchased Canadian AI startup DarwinAI according to a Bloomberg report today. Apparently the deal was done early this year but still hasn’t been publicly announced according to the report. Apple is preparing Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimization algorithms to iteratively refine their parameters until Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, code-named Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Nvidia Showcases Quantum Cloud, Expanding Quantum Portfolio at GTC24

March 18, 2024

Nvidia’s barrage of quantum news at GTC24 this week includes new products, signature collaborations, and a new Nvidia Quantum Cloud for quantum developers. Wh Read more…

Houston We Have a Solution: Addressing the HPC and Tech Talent Gap

March 15, 2024

Generations of Houstonian teachers, counselors, and parents have either worked in the aerospace industry or know people who do - the prospect of entering the fi Read more…

Survey of Rapid Training Methods for Neural Networks

March 14, 2024

Artificial neural networks are computing systems with interconnected layers that process and learn from data. During training, neural networks utilize optimizat Read more…

PASQAL Issues Roadmap to 10,000 Qubits in 2026 and Fault Tolerance in 2028

March 13, 2024

Paris-based PASQAL, a developer of neutral atom-based quantum computers, yesterday issued a roadmap for delivering systems with 10,000 physical qubits in 2026 a Read more…

India Is an AI Powerhouse Waiting to Happen, but Challenges Await

March 12, 2024

The Indian government is pushing full speed ahead to make the country an attractive technology base, especially in the hot fields of AI and semiconductors, but Read more…

Charles Tahan Exits National Quantum Coordination Office

March 12, 2024

(March 1, 2024) My first official day at the White House Office of Science and Technology Policy (OSTP) was June 15, 2020, during the depths of the COVID-19 loc Read more…

AI Bias In the Spotlight On International Women’s Day

March 11, 2024

What impact does AI bias have on women and girls? What can people do to increase female participation in the AI field? These are some of the questions the tech Read more…

Alibaba Shuts Down its Quantum Computing Effort

November 30, 2023

In case you missed it, China’s e-commerce giant Alibaba has shut down its quantum computing research effort. It’s not entirely clear what drove the change. Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Analyst Panel Says Take the Quantum Computing Plunge Now…

November 27, 2023

Should you start exploring quantum computing? Yes, said a panel of analysts convened at Tabor Communications HPC and AI on Wall Street conference earlier this y Read more…

Shutterstock 1285747942

AMD’s Horsepower-packed MI300X GPU Beats Nvidia’s Upcoming H200

December 7, 2023

AMD and Nvidia are locked in an AI performance battle – much like the gaming GPU performance clash the companies have waged for decades. AMD has claimed it Read more…

DoD Takes a Long View of Quantum Computing

December 19, 2023

Given the large sums tied to expensive weapon systems – think $100-million-plus per F-35 fighter – it’s easy to forget the U.S. Department of Defense is a Read more…

Synopsys Eats Ansys: Does HPC Get Indigestion?

February 8, 2024

Recently, it was announced that Synopsys is buying HPC tool developer Ansys. Started in Pittsburgh, Pa., in 1970 as Swanson Analysis Systems, Inc. (SASI) by John Swanson (and eventually renamed), Ansys serves the CAE (Computer Aided Engineering)/multiphysics engineering simulation market. Read more…

Intel’s Server and PC Chip Development Will Blur After 2025

January 15, 2024

Intel's dealing with much more than chip rivals breathing down its neck; it is simultaneously integrating a bevy of new technologies such as chiplets, artificia Read more…

Baidu Exits Quantum, Closely Following Alibaba’s Earlier Move

January 5, 2024

Reuters reported this week that Baidu, China’s giant e-commerce and services provider, is exiting the quantum computing development arena. Reuters reported � Read more…

Leading Solution Providers

Contributors

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

Training of 1-Trillion Parameter Scientific AI Begins

November 13, 2023

A US national lab has started training a massive AI brain that could ultimately become the must-have computing resource for scientific researchers. Argonne N Read more…

Shutterstock 1179408610

Google Addresses the Mysteries of Its Hypercomputer 

December 28, 2023

When Google launched its Hypercomputer earlier this month (December 2023), the first reaction was, "Say what?" It turns out that the Hypercomputer is Google's t Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

AMD MI3000A

How AMD May Get Across the CUDA Moat

October 5, 2023

When discussing GenAI, the term "GPU" almost always enters the conversation and the topic often moves toward performance and access. Interestingly, the word "GPU" is assumed to mean "Nvidia" products. (As an aside, the popular Nvidia hardware used in GenAI are not technically... Read more…

Shutterstock 1606064203

Meta’s Zuckerberg Puts Its AI Future in the Hands of 600,000 GPUs

January 25, 2024

In under two minutes, Meta's CEO, Mark Zuckerberg, laid out the company's AI plans, which included a plan to build an artificial intelligence system with the eq Read more…

Google Introduces ‘Hypercomputer’ to Its AI Infrastructure

December 11, 2023

Google ran out of monikers to describe its new AI system released on December 7. Supercomputer perhaps wasn't an apt description, so it settled on Hypercomputer Read more…

China Is All In on a RISC-V Future

January 8, 2024

The state of RISC-V in China was discussed in a recent report released by the Jamestown Foundation, a Washington, D.C.-based think tank. The report, entitled "E Read more…

HPCwire