tag: compute-in-memory accelerator

PLANAR: A Programmable Accelerator For Near-Memory Data Rearrangement

By Arm - 12 Oct, 2022 - Comments: 0

Many applications employ irregular and sparse memory accesses that cannot take advantage of existing cache hierarchies in high performance processors. To solve this problem, Data Layout Transformation (DLT) techniques rearrange sparse data into a dense representation, improving locality and cache utilization. However, prior proposals in this space fail to provide a design that (i) scales with m... » read more

Spiking Neural Networks Place Data In Time

By Katherine Derbyshire - 16 Jul, 2020 - Comments: 0

Artificial neural networks have found a variety of commercial applications, from facial recognition to recommendation engines. Compute-in-memory accelerators seek to improve the computational efficiency of these networks by helping to overcome the von Neumann bottleneck. But the success of artificial neural networks also highlights their inadequacies. They replicate only a small subset of th... » read more

Trending Articles

Hybrid Bonding Makes Strides Toward Manufacturability

Companies are selecting preferred flows, but the process details are changing rapidly to meet the needs of different applications.

by Laura Peters

Americas Chip Funding Energizes Industry

Massive government infusions aim to improve security and supply chain robustness.

Advanced Packaging Driving New Collaboration Across Supply Chain

Rising complexity is changing the way companies engage and interact, but long-standing barriers in communication, culture, and IP protection are slowing progress.

by Gregory Haley

Chiplets Make Progress Using Interconnects As Glue

Industry learning expands as more SoCs are disaggregated at leading edge, opening door to more third-party chiplets.

by Ann Mutschler

2D Semiconductors Make Progress, But So Does Silicon

Can 2D materials be fabricated consistently at a cost that competes with silicon?

by Katherine Derbyshire

Knowledge Centers
Entities, people and technologies explored

Related Articles

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

GDDR7 Memory Supercharges AI Inference

High bandwidth and low latency are paramount for AI-powered edge and endpoints.

by Tim Messegee

CPU Performance Bottlenecks Limit Parallel Processing Speedups

Hardware optimizations and well-thought-out software architectures can help, but only incrementally.

by Bryon Moyer

Fantastical Creatures

Why HLS is critical for determining which type of processors to use.

by Russell Klein

Is PPA Relevant Today?

Power, performance, and area/cost have been the three optimization targets for decades, but are they pertinent for today's complex systems?

by Brian Bailey

Power Delivery Challenged By Data Center Architectures

More powerful servers are required to crunch more data, but getting power to those servers is becoming complicated.

by Ann Mutschler

CXL Thriving As Memory Link

Adoption of Compute Express Link protocol spreads as way to connect memories.

by Karen Heyman

Higher Density, More Data Create New Bottlenecks In AI Chips

More options are available, but each comes with tradeoffs and adds to complexity.

by Adam Kovac

About

Navigation

Connect With Us

Facebook
Twitter @semiEngineering
LinkedIn
YouTube

Copyright ©2013-2024 SMG | Terms of Service | Privacy Policy