Generative AI Training With HBM3 Memory


One of the biggest, most talked about application drivers of hardware requirements today is the rise of Large Language Models (LLMs) and the generative AI which they make possible.  The most well-known example of generative AI right now is, of course, ChatGPT. ChatGPT’s large language model for GPT-3 utilizes 175 billion parameters. Fourth generation GPT-4 will reportedly boost the number of... » read more

Solving Memory Mapping Issues with Deep RL (Google)


A technical paper titled "Optimizing Memory Mapping Using Deep Reinforcement Learning" was published by Google DeepMind and Google. Abstract: "Resource scheduling and allocation is a critical component of many high impact systems ranging from congestion control to cloud computing. Finding more optimal solutions to these problems often has significant impact on resource and time savings, red... » read more

Server Design With Pin-Efficient CXL Interface (Georgia Tech)


A new technical paper titled "A Case for CXL-Centric Server Processors" was written by researchers at Georgia Tech. Abstract: "The memory system is a major performance determinant for server processors. Ever-growing core counts and datasets demand higher bandwidth and capacity as well as lower latency from the memory system. To keep up with growing demands, DDR--the dominant processor inter... » read more

Pinpointing Timing Delays Can Improve Chip Reliability


Growing pressure to improve IC reliability in safety- and mission-critical applications is fueling demand for custom automated test pattern generation (ATPG) to detect small timing delays, and for chip telemetry circuits that can assess timing margin over a chip's lifetime. Knowing the timing margin in signal paths has become an essential component in that reliability. Timing relationships a... » read more

Automated Tool Flow From Domain-Specific Languages To Generate Massively Parallel Accelerators on HBM-Equipped FPGAs


A new technical paper titled "Automatic Creation of High-bandwidth Memory Architectures from Domain-specific Languages: The Case of Computational Fluid Dynamics" was published by researchers at Politecnico di Milano and TU Dresden. The paper states "In this article, we propose an automated tool flow from a domain-specific language for tensor expressions to generate massively parallel acceler... » read more

Tech Forecast: Fab Processes To Watch Through 2040


The massive proliferation of semiconductors in more markets, and more applications within those markets, is expected to propel the industry to more than $1 trillion by 2030. But over the next 17 years, semiconductors will reach well beyond the numbers, changing the way people work, how they communicate, and how they measure and monitor their health and well-being. Chips will be the enabling ... » read more

Will AI Take My Job?


Everyone is talking about ChatGPT these days, and I am sure we will be comparing it with Google's new offering before long. I thought it was time that I gave it a quick spin, and since I am preparing to moderate a webinar about chiplets as I write this, I decided it was a good example of a fairly new field and would be a good test. I started by asking, "What are semiconductor chiplets, what ... » read more

HBM-Enabled FPGA-Based Graph Processing Accelerator


A technical paper titled "ACTS: A Near-Memory FPGA Graph Processing Framework" was published by researchers at University of Virginia and Samsung. Abstract: "Despite the high off-chip bandwidth and on-chip parallelism offered by today's near-memory accelerators, software-based (CPU and GPU) graph processing frameworks still suffer performance degradation from under-utilization of available ... » read more

Advanced Packaging for High-Bandwidth Memory: Influences of TSV size, TSV Aspect Ratio And Annealing Temperature


A technical paper titled "Stress Issue of Vertical Connections in 3D Integration for High-Bandwidth Memory Applications" was published by researchers at National Yang Ming Chiao Tung University. Abstract: "The stress of TSV with different dimensions under annealing condition has been investigated. Since the application of TSV and bonding technology has demonstrated a promising approach for ... » read more

Where Power Is Spent In HBM


HBM is gaining ground because of a spike in the amount of data that needs to be processed quickly, but big reductions in power are possible if that processing can be moved closer to the HBM modules, and if more can be done in each compute cycle without sending data back and forth to memory as frequently. Steven Woo, fellow and distinguished engineer at Rambus, talks about what can be done to bo... » read more

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