The Silicon Review
Data is fastbecoming one of the world’s most valuable commodities. It enables, empowers and entertains people. It is a staple of everyone’s daily lives, and the confidence with which the world interacts with data is fundamental to how it functions as a society. Data is at the core of everything Rambus does: moving it, accelerating it, and securing it. And its mission is to make it faster, safer and smarter. Rambus is a diversified technology company, specializing in the performance and protection of data. From IP cores and chips to IoT security services, to smart transit and mobile payment software, its portfolio of products positively impacts the modern world. Dedicated to serving the demanding applications from the data center to the mobile edge, its core divisions combine to offer a broad suite of solutions that span memory and interfaces, security, and emerging technologies. Rambus collaborates with its customers and partners to create cutting-edge IP that can be rapidly implemented by fabless and fully-integrated semiconductor companies. Its comprehensive product portfolio spans solutions for memory and interfaces to security, payments, and ticketing.
Payments + Tokenization
Retail & E-Commerce Payments
CryptoManager Security Platform
Cryogenic Memory: A research program focused on cryogenic temperature computing as an avenue to surpass the slowing of Moore’s Law for next-generation data centers in the age of Big Data and cloud computing.
Rambus is researching opportunities to optimize memory and interface solutions for operation at cryogenic temperatures for future generation datacenters. In a manner similar to “Moore’s Law” memory systems have shown exponential improvements in energy efficiency, density and per-bit cost for decades. These gains have made possible the rapid growth in centralized computing commonly referred to as cloud computing. Recently, however, the scaling of these metrics through conventional techniques has slowed, while at the same time demand for larger, faster data systems has increased by the proliferation of big data applications including data analytics and machine learning. Therefore the industry seeks step function changes in performance and cryogenic computing and/or quantum computing are potential breakthrough solutions that could lead to a new era in computing. The potential improvements in cycle time, power consumption, and higher compute density are all requirements for the most demanding applications and are all potential outcomes of its cryogenic research.
This work is an exploration to determine if there are sufficient energy saving opportunities or other advantages for memory systems operating at low temperatures. While energy consumption is a primary area of emphasis, bit density scaling, performance, cost per bit, and manufacturability may also benefit from reduced temperature and are being investigated. This would create an environment for potential computation speed increases at reduced power consumption. Today there are multiple public and private sector research projects around cryogenic computing as well as quantum computing. These efforts show high-speed processes capable of manipulating large amounts of data, which creates a multiple order of magnitude gap in the speed at which data can be sent or received from that process. There is also a temperature gap between room temperature operation of current supercomputers (approximately 300K) and the operating temperature of a cryogenic core (4K). Rambus is seeking to close these gaps by designing and developing optimized memory sub-system solutions, capable of operating at 77K and interfacing to computers operating at liquid helium temperatures (4K).
Hybrid Memory Research: A research program, in partnership with IBM, to explore the use of DRAM with emerging memories (EM) to create a high-capacity memory subsystem that delivers comparable performance to DRAM.Leading-edge technologies, such as big data analytics and deep learning (a specific subset of artificial intelligence), are creating an increasing demand for memory capacity and performance inside the data center. For example, deep learning techniques that leverage neural networks are being used in autonomous driving applications for voice or facial recognition and are required to analyze and compute large data sets at incredible speeds. Due to this, the memory bandwidth and capacity in the system directly define the run time of a learning algorithm and are often the limiting factor for the system’s performance.
In addition to these emerging technologies, there are also many current applications that could benefit from a cost-effective way to significantly increase memory capacity. Examples include in-memory databases (IMDB) for faster decision making, media streaming services that could load full movies into memory, large graphics rendering projects (animated movie or game creation) that constantly require terabytes of data to be loaded into memory at a time and more. Credit card fraud detection is a great example use case that could benefit from large-capacity IMBDs. The bank behind a credit card is required to approve or reject a transaction from any user at any given moment in time, which requires them to quickly access large amounts of information every transaction.
Beyond DDR4: Next-Generation Main Memory: Focused on advancing single-ended signaling technologies to meet the memory system requirements of next-generation computing applications while maintaining compatibility with current industry standard DDR4 solutions, this next-generation R+ main memory architecture advances single-ended signaling up to 6.4 gigabits per second (Gbps) in a multi-rank, multi-DIMM system.
Meet the Leader
Luc Seraphin, President, and Chief Executive Officer: With over 20 years of experience managing global businesses, Luc brings the overall vision and leadership necessary to drive future growth for the company. Prior to this role, Luc was the senior vice president and general manager of the Memory and Interface Division, leading the development of the company’s innovative memory architectures and high-speed serial link solutions. Luc also served as the senior vice president of Worldwide Sales and Operations where he oversaw sales, business development, customer support, and operations across the various business units within Rambus.
Luc started his career as a field application engineer at NEC and later joined AT&T Bell Labs, which became Lucent Technologies and Agere Systems (now Avago Technologies). During his 18 years at Avago, Luc held several senior positions in sales, marketing, and general management, culminating in his last position as executive vice president and general manager of the Wireless Business Unit. Following this, Luc held the position of general manager of a GPS startup company in Switzerland and was vice president of Worldwide Sales and Support at Sequans Communications. During his career, Luc has advised and supported companies in both the product and IP markets.
Luc holds a bachelor’s degree in Mathematics and Physics and a master’s degree in Electrical Engineering from EcoleSuperieure de Chimie, Physique, Electronique, based in Lyon, France where he majored in Computer Architecture. Luc also holds an MBA from the University of Hartford and has completed the senior executive program of Columbia University.