tag: Quadric

When To Expect Domain-Specific AI Chips
By Brian Bailey - 13 Jun, 2024 - Comments: 0

The chip industry is moving toward domain-specific computation, while artificial intelligence (AI) is moving in the opposite direction, creating a gap that could force significant changes in how chips and systems are architected in the future. Behind this split is the amount of time it takes to design hardware and software. In the 18 months since ChatGPT was launched on the world, there has ... » read more

Will Domain-Specific ICs Become Ubiquitous?
By Brian Bailey - 16 May, 2024 - Comments: 0

Questions are surfacing for all types of design, ranging from small microcontrollers to leading-edge chips, over whether domain-specific design will become ubiquitous, or whether it will fall into the historic pattern of customization first, followed by lower-cost, general-purpose components. Custom hardware always has been a double-edged sword. It can provide a competitive edge for chipmake... » read more

Running More Efficient AI/ML Code With Neuromorphic Engines
By Karen Heyman - 16 May, 2024 - Comments: 0

Neuromorphic engineering is finally getting closer to market reality, propelled by the AI/ML-driven need for low-power, high-performance solutions. Whether current initiatives result in true neuromorphic devices, or whether devices will be inspired by neuromorphic concepts, remains to be seen. But academic and industry researchers continue to experiment in the hopes of achieving significant ... » read more

Power/Performance Costs In Chip Security
By Adam Kovac - 16 May, 2024 - Comments: 0

Hackers ranging from hobbyists to corporate spies and nation states are continually poking and prodding for weaknesses in data centers, cars, personal computers, and every other electronic device, resulting in a growing effort to build security into chips and electronic systems. The current estimate is that 60% of chips and systems have some type of security built in, and that percentage is ... » read more

Fallback Fails Spectacularly
By Steve Roddy - 16 May, 2024 - Comments: 0

Conventional AI/ML inference silicon designs employ a dedicated, hardwired matrix engine – typically called an “NPU” – paired with a legacy programmable processor – either a CPU, or DSP, or GPU. The common theory behind these two-core (or even three core) architectures is that most of the matrix-heavy machine learning workload runs on the dedicated accelerator for maximum efficienc... » read more

Is The Transformer Era Over?
By Quadric.io - 15 May, 2024 - Comments: 0

The idea of transformer networks has existed since the seminal publication of the Attention is All You Need paper by Google researchers in June 2017.  And while transformers quickly gained traction within the ML research community, and in particular demonstrated superlative results in vision applications (ViT paper), transformer networks were definitely not a topic of trendy conversation ar... » read more

Fundamental Issues In Computer Vision Still Unresolved
By Karen Heyman - 02 May, 2024 - Comments: 1

Given computer vision’s place as the cornerstone of an increasing number of applications from ADAS to medical diagnosis and robotics, it is critical that its weak points be mitigated, such as the ability to identify corner cases or if algorithms are trained on shallow datasets. While well-known bloopers are often the result of human decisions, there are also fundamental technical issues that ... » read more

Dealing With AI/ML Uncertainty
By Karen Heyman - 25 Apr, 2024 - Comments: 0

Despite their widespread popularity, large language models (LLMs) have several well-known design issues, the most notorious being hallucinations, in which an LLM tries to pass off its statistics-based concoctions as real-world facts. Hallucinations are examples of a fundamental, underlying issue with LLMs. The inner workings of LLMs, as well as other deep neural nets (DNNs), are only partly kno... » read more

Architecting Chips For High-Performance Computing
By Ann Mutschler - 15 Apr, 2024 - Comments: 0

The world’s leading hyperscaler cloud data center companies — Amazon, Google, Meta, Microsoft, Oracle, and Akamai — are launching heterogeneous, multi-core architectures specifically for the cloud, and the impact is being felt in high-performance CPU development across the chip industry. It's unlikely that any these chips will ever be sold commercially. They are optimized for specific ... » read more

Hybrid Architecture Blends Best Of Both Worlds
By Steve Roddy - 11 Apr, 2024 - Comments: 0

Quadric chose the brand name Chimera to describe the company’s novel general purpose neural processing unit (GPNPU) architecture. According to the online Oxford dictionary, in biology a chimera is “an organism containing a mixture of genetically different tissues (or DNA).” Quadric made that naming choice to reflect the fact that its Chimera GPNPU has characteristics of both conventiona... » read more

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