In-Memory Computing Challenges Come Into Focus

By Katherine Derbyshire - 06 Feb, 2019 - Comments: 6

For the last several decades, gains in computing performance have come by processing larger volumes of data more quickly and with superior precision. Memory and storage space are measured in gigabytes and terabytes now, not kilobytes and megabytes. Processors operate on 64-bit rather than 8-bit chunks of data. And yet the semiconductor industry’s ability to create and collect high quality ... » read more

Mostly Upbeat Outlook For Chips

By Brian Bailey - 17 Jan, 2019 - Comments: 1

2019 has started with cautious optimism for the semiconductor industry, despite dark clouds that dot the horizon. Market segments such as cryptocurrencies and virtual reality are not living up to expectations, the market for smart phones appears to be saturated, and DRAM prices are dropping, leading to cut-backs in capital expenditures. EDA companies are talking about sales to China being pu... » read more

AI Market Ramps Everywhere

By Brian Bailey - 20 Dec, 2018 - Comments: 0

Artificial Intelligence (AI) has inspired the general populace, but its rapid rise over the past few years has given many people pause. From realistic concerns about robots taking over jobs to sci-fi scares about robots more intelligent than humans building ever smarter robots themselves, AI inspires plenty of angst. Within the technology industry, we have a better understanding about the pote... » read more

High Neural Inferencing Throughput At Batch=1

By Geoff Tate - 06 Dec, 2018 - Comments: 0

Microsoft presented the following slide as part of their Brainwave presentation at Hot Chips this summer: In existing inferencing solutions, high throughput (and high % utilization of the hardware) is possible for large batch sizes: this means that instead of processing say one image at a time, the inferencing engine processes say 10 or 50 images in parallel. This minimizes the number of... » read more

Inferencing In Hardware

By Ed Sperling - 06 Dec, 2018 - Comments: 0

Cheng Wang, senior vice president of engineering at Flex Logix, examines shifting neural network models, how many multiply-accumulates are needed for different applications, and why programmable neural inferencing will be required for years to come. https://youtu.be/jb7qYU2nhoo See other tech talk videos here. » read more

Power/Performance Bits: Nov. 20

By Jesse Allen - 20 Nov, 2018 - Comments: 0

In-memory compute accelerator Engineers at Princeton University built a programmable chip that features an in-memory computing accelerator. Targeted at deep learning inferencing, the chip aims to reduce the bottleneck between memory and compute in traditional architectures. The team's key to performing compute in memory was using capacitors rather than transistors. The capacitors were paire... » read more

The Week In Review: Design

By Jesse Allen - 02 Nov, 2018 - Comments: 0

M&A GlobalFoundries formed Avera Semiconductor, a wholly-owned subsidiary focused on custom ASIC designs. While Avera will use its relationship with GF for 14/12nm and more mature technologies, it has a foundry partnership lined up for 7nm. The new company's IP portfolio includes high-speed SerDes, high-performance embedded TCAMs, ARM cores and performance and density-optimized embedded SR... » read more

Real-Time Object Recognition At Low Cost/Power/Latency

By Geoff Tate - 01 Nov, 2018 - Comments: 0

Most neural network chips and IP talk about ResNet-50 benchmarks (image classification at 224x224 pixels). But we find that the number one neural network of interest for most customers is real-time object recognition, such as YOLOv3. It's not possible to do comparisons here because nobody shows a YOLOv3 benchmark for their inferencing. But it's very possible to improve on the inferencing per... » read more

Making AI Run Faster

By Ed Sperling - 11 Oct, 2018 - Comments: 0

The semiconductor industry has woken up to the fact that heterogeneous computing is the way forward and that inferencing will require more than a GPU or a CPU. The numbers being bandied about by the 30 or so companies working on this problem are 100X improvements in performance. But how to get there isn't so simple. It requires four major changes, as well as some other architectural shifts. ... » read more

Using ASICs For AI Inferencing

By Ed Sperling - 10 Oct, 2018 - Comments: 0

Flex Logix’s Cheng Wang looks at why ASICs are the best way to improve performance and optimize power and area for inferencing, and how to add flexibility into those designs to deal with constantly changing algorithms and data sets. https://youtu.be/XMHr7sz9JWQ » read more

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Knowledge Centers
Entities, people and technologies explored

Shift Left Is The Tip Of The Iceberg

A transformative change is underway for semiconductor design and EDA. New languages, models, and abstractions will need to be created.

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Partitioning In The Chiplet Era

Understanding how chiplets interact under different workloads is critical to ensuring signal integrity and optimal performance in heterogeneous designs.

by Ann Mutschler

3.5D: The Great Compromise

Pros and cons of a middle-ground chiplet assembly that combines 2.5D and 3D-IC.

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AI’s Role In Chip Design Widens, Drawing In New Startups

Focus is on letting engineers do much more with the same or fewer resources — and less drudgery.

by Karen Heyman

Key Technologies To Extend EUV To 14 Angstroms

Alongside high-NA EUV will be better-performing photoresists, reduced roughness using passivation and etch, and lateral etching to reduce tip-to-tip dimensions.

by Laura Peters

What Comes After HBM For Chiplets

The standard for high-bandwidth memory limits design freedom at many levels, but that is required for interoperability. What freedoms can be taken from other functions to make chiplets possible?

by Brian Bailey

Memory Fundamentals For Engineers

eBook: Nearly everything you need to know about memory, including detailed explanations of the different types of memory; how and where these are used today; what's changing, which memories are successful and which ones might be in the future; and the limitations of each memory type.

by The SE Staff

Why Small Fab And Assembly Houses Are Thriving

Megafabs churning out the most advanced processors are not the only game in town.

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tag: inferencing