How Inferencing Differs From Training in Machine Learning Applications


Machine learning (ML)-based approaches to system development employ a fundamentally different style of programming than historically used in computer science. This approach uses example data to train a model to enable the machine to learn how to perform a task. ML training is highly iterative with each new piece of training data generating trillions of operations. The iterative nature of the tr... » read more

What Is An xPU?


Almost every day there is an announcement about a new processor architecture, and it is given a three-letter acronym — TPU, IPU, NPU. But what really distinguishes them? Are there really that many unique processor architectures, or is something else happening? In 2018, John L. Hennessy and David A. Patterson delivered the Turing lecture entitled, "A New Golden Age for Computer Architecture... » read more

Changing Server Architectures In The Data Center


Data centers are undergoing a fundamental shift to boost server utilization and improve efficiency, optimizing architectures so available compute resources can be leveraged wherever they are needed. Traditionally, data centers were built with racks of servers, each server providing computing, memory, interconnect, and possibly acceleration resources. But when a server is selected, some of th... » read more

HBM3: Big Impact On Chip Design


An insatiable demand for bandwidth in everything from high-performance computing to AI training, gaming, and automotive applications is fueling the development of the next generation of high-bandwidth memory. HBM3 will bring a 2X bump in bandwidth and capacity per stack, as well as some other benefits. What was once considered a "slow and wide" memory technology to reduce signal traffic dela... » read more

Leaky Buddies: Cross-Component Covert Channels on Integrated CPU-GPU Systems


Find Technical Paper link here. Abstract: "Graphics Processing Units (GPUs) are ubiquitous components used across the range of today’s computing platforms, from phones and tablets, through personal computers, to high-end server class platforms. With the increasing importance of graphics and video workloads, recent processors are shipped with GPU devices that are integrated on the same chi... » read more

Efficient Multi-GPU Shared Memory via Automatic Optimization of Fine-Grained Transfers


Harini Muthukrishnan (U of Michigan); David Nellans, Daniel Lustig (NVIDIA); Jeffrey A. Fessler, Thomas Wenisch (U of Michigan). Abstract—"Despite continuing research into inter-GPU communication mechanisms, extracting performance from multiGPU systems remains a significant challenge. Inter-GPU communication via bulk DMA-based transfers exposes data transfer latency on the GPU’s critical... » read more

Architectural Considerations For AI


Custom chips, labeled as artificial intelligence (AI) or machine learning (ML), are appearing on a weekly basis, each claiming to be 10X faster than existing devices or consume 1/10 the power. Whether that is enough to dethrone existing architectures, such as GPUs and FPGAs, or whether they will survive alongside those architectures isn't clear yet. The problem, or the opportunity, is that t... » read more

CEO Outlook: More Data, More Integration, Same Deadlines


Experts at the Table: Semiconductor Engineering sat down to discuss the future of chip design and EDA tools with Lip-Bu Tan, CEO of Cadence; Simon Segars, CEO of Arm; Joseph Sawicki, executive vice president of Siemens IC EDA; John Kibarian, CEO of PDF Solutions; Prakash Narain, president and CEO of Real Intent; Dean Drako, president and CEO of IC Manage; and Babak Taheri, CEO of Silvaco. What ... » read more

Tradeoffs To Improve Performance, Lower Power


Generic chips are no longer acceptable in competitive markets, and the trend is growing as designs become increasingly heterogeneous and targeted to specific workloads and applications. From the edge to the cloud, including everything from vehicles, smartphones, to commercial and industrial machinery, the trend increasingly is on maximizing performance using the least amount of energy. This ... » read more

DRAM’s Persistent Threat To Chip Security


A well-known DRAM vulnerability called "rowhammer," which allows an assailant to disrupt or take control of a system, continues to haunt the chip industry. Solutions have been tried, and new ones are being proposed, but the potential for a major attack persists. First discovered some five years ago, most of the efforts to eliminate the "rowhammer" threat have done little more than mitigate t... » read more

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