Accelerating AI And ML Applications With PCIe 5


The rapid adoption of sophisticated artificial intelligence/machine learning (AI/ML) applications and the shift to cloud-based workloads has significantly increased network traffic in recent years. Historically, the intensive use of virtualization ensured that server compute capacity adequately met the need of heavy workloads. This was achieved by dividing or partitioning a single (physical) se... » read more

GDDR6 Pushes The Memory Envelope For AI And ADAS


Memory bandwidth is an ever-increasing critical bottleneck for a wide range of use cases and applications. These include artificial intelligence (AI), machine learning (ML), advanced driver-assistance systems (ADAS), as well as 5G wireless and wireline infrastructure. In addition to memory bottlenecks, the above-mentioned use cases and applications are rapidly hitting the real-world limits of t... » read more

Accelerating Chiplets With 112G XSR SerDes PHYs


The fading of Moore’s Law and an almost exponential increase in data is challenging the semiconductor industry as never before. Indeed, zettabytes of data are constantly generated by a wide range of devices including IoT endpoints such as vehicles, wearables, smartphones and appliances. Moreover, sophisticated artificial intelligence (AI) and machine learning (ML) applications are adding new ... » read more

Breaking Down The AI Memory Wall


Over the past few decades, the semiconductor industry has witnessed the rapid evolution of memory technology as new memories helped to usher in new usage models that characterized each decade. For example, synchronous memory helped drive the personal computer (PC) revolution in the 1990s, and this was quickly followed by specialized graphics memory (GPUs) for game consoles in the 2000s. When sm... » read more

OIF Eyes Expanded Electrical Link Definitions For 112 Gbps


The insatiable demand for more bandwidth, lower latencies, and higher speeds is driven by a diverse range of applications and use cases. These include artificial intelligence /machine learning, sophisticated ADAS systems for semi-autonomous vehicles, 4K-8K video streaming, eSports, and AR/VR. With global IP traffic now measured in zettabytes (ZB) per year, hyperscalers and service providers ... » read more

GDDR Accelerates Artificial Intelligence And Machine Learning


The origins of modern graphics double data rate (GDDR) memory can be traced back to GDDR3 SDRAM. Designed by ATI Technologies, GDDR3 made its first appearance in NVidia’s GeForce FX 5700 Ultra card which debuted in 2004. Offering reduced latency and high bandwidth for GPUs, GDDR3 was followed by GDDR4, GDDR5, GDDR5X and the latest generation of GDDR memory, GDDR6. GDDR6 SGRAM supports a ma... » read more

HBM2e Offers Solid Path For AI Accelerators


Today, AI processors are so blazingly fast that they’re constantly having to wait for data from memory. Unfortunately, with the status quo, memory is just not fast enough to unleash the true performance of those new and highly advancing AI processors. In simple terms, AI processor performance is rapidly growing, and memory is not keeping up. This creates a bottleneck, or what Rambus calls the... » read more

Engineering The Signal For GDDR6


DDR1 through DDR3 had their challenges, but speeds were below one gigabit and signal integrity (SI) challenges were more centered around static timing and running pseudo random binary sequence (PRBS) simulations. Now, with GDDR6, we are working on 16 to 20 gigabits per second (Gbps) signaling and even faster in the near future. As a result, engineering the signal for GDDR6 will require careful ... » read more

GDDR6 And HBM2: Signal Integrity Challenges For AI


In a nutshell, Artificial Intelligence (AI) and its growing list of applications demand a considerably large amount of bandwidth to push bits in and out of memory at the highest speeds possible. AI has been getting a lot of industry attention, and certainly it’s not a new phenomenon because it’s been gaining even greater traction in the last year or two. This is especially true since a n... » read more

GDDR6: Signal Integrity Challenges For Automotive Systems


Signal integrity (SI) is at the forefront of SoC and system designers’ thinking as they plan for upcoming high-speed GDDR6 DRAM and PHY implementations for automotive and advanced driver assistance system (ADAS) applications. Rambus and its partners are closely looking at how GDDR6’s 16 gigabit per second speed at each pin affects signal integrity given the cost and system constraints for a... » read more

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