Achronix Chooses Rambus GDDR6 PHY IP for Next-Generation FPGA

Rambus Inc. (NASDAQ: RMBS) today announced that Achronix Semiconductor Corporation, a leader in FPGA-based hardware data acceleration devices and high-performance eFGPA IP, has selected the Rambus GDDR6 PHY for its next-generation Speedster7t FPGA family. Leveraging the top-end data rates delivered by the Rambus GDDR6 memory interface, the Speedster7t family is optimized for artificial intelligence (AI), machine learning (ML) and high-bandwidth data acceleration applications and workloads.

Designed for performance and power efficiency, the Rambus GDDR6 PHY is beneficial for advanced driver-assistance systems (ADAS), AI, ML, graphics and networking applications. Rambus’ GDDR6 PHY enables the communication to and from high-speed, high-bandwidth GDDR6 SDRAM memory, which is a high-performance memory solution that can be used in a variety of applications that require large amounts of data computation.

"GDDR6 is emerging as a mainstream memory solution for high-performance AI/ML and networking applications, and, in utilizing Rambus’ GDDR6 PHY IP, Achronix is an early leader in adopting the technology to differentiate its next generation of products,” said Hemant Dhulla, vice president and general manager of IP Cores at Rambus. "We are excited to be working with Achronix to expand its portfolio of high-performance FPGA solutions, including its latest Speedster 7t family.”

The Rambus GDDR6 PHY is the fastest memory IP on the market, at 16 Gbps. Leveraging its strong signal integrity and system design expertise, Rambus worked closely with Achronix on their package design, to support the eight GDDR6 IP controllers on the first Speedster7t device. Providing up to 4 Tbps of performance, the new Speedster 7t FPGAs include a revolutionary new 2D network-on-chip (NoC) and a high-density array of new machine learning processors (MLP). Merging FPGA programmability with ASIC routing structures and compute engines, the Speedster7t family creates a new "FPGA+” class of technology, pushing the boundaries of high-performance compute acceleration.

"New use cases for GDDR6 such as AI/ML require extremely fast data transfer between memory and compute,” said Steve Mensor, vice president of marketing, Achronix. "Rambus’ GDDR6 PHY IP will enable Achronix’ Speedster7t FPGA family to support these high-performance data acceleration applications at a low cost with low latency, allowing it to process complex data loads quickly and efficiently.”

For more information on our latest Rambus GDDR6 high speed memory offerings, please visit www.rambus.com/gddr6. Or, visit Achronix in Booth 861 at the Design Automation Conference (DAC) in Las Vegas, NV from June 2 – 6, 2019 to learn more.

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About Rambus Memory and Interfaces Division

The Rambus Memory and Interfaces Division develops products and services that solve the power, performance, and capacity challenges of the communications and data center computing markets. Rambus enhanced standards-compatible and custom memory and serial link solutions include chips, architectures, memory and SerDes interfaces, IP validation tools, and system and IC design services. Developed through our system-aware design methodology, Rambus products deliver improved time-to-market and first-time-right quality.

About Rambus Inc.

Dedicated to making data faster and safer, Rambus creates innovative hardware, software and services that drive technology advancements from the data center to the mobile edge. Our architecture licenses, IP cores, chips, software, and services span memory and interfaces, security, and emerging technologies to positively impact the modern world. We collaborate with the industry, partnering with leading chip and system designers, foundries, and service providers. Integrated into tens of billions of devices and systems, our products and technologies power and secure diverse applications, including Big Data, Internet of Things (IoT) security, mobile payments, and smart ticketing. For more information, visit rambus.com.

Source: Rambus Inc.

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