For the last two years, in January, I have published my predictions about the new AI silicon I expect in the coming year. Like the weatherman, I’ve gotten some details wrong but I’ve been reasonably accurate, at least directionally. So, here we go again with a look at likely 2021 advancements and possible failures. I …
One would think, or hope, that a startup shipping its second-generation AI chips and software stack would be content to have over $200M in the bank to fund future development and market penetration. For UK AI startup Graphcore, that is a lot of money. When you are a darling in a fast-growing land grab, though, …
Product Lifecycle Management offerings have helped companies manage their product lifecycles for decades, reducing costs, improving quality and making customers happy. Surprisingly, though, such a process is not in place for the silicon chips used in almost everything these days. While the semiconductor industry has matured on many fronts, producing vast quantities of faster, cheaper …
Never Heard Of Silicon Lifecycle Management? Join The Club. Read More »
AWS’s annual re:Invent conference this year included big news from CEO Andy Jassy and AI VP Swami Sivasubramanian. AWS launched two new hardware platforms for AI and significantly expanded its SageMaker software to simplify running AI models on AWS at maximum performance. When I look at the breadth of AI software, the depth of AI …
There’s been a lot of news lately on the AI chip front, so I wanted to share a short synopsis of what has been happening for anyone who may be distracted by the holidays. I will flesh these stories out further before my annual Cambrian AI Explosion blog in January here on Forbes. Let’s start with the …
Qualcomm announced the first shipments of the Cloud AI 100 family of products, thus entering the data center, cloud edge, edge appliance and 5G infrastructure markets for accelerated artificial intelligence (AI) processing. Qualcomm has demonstrated its AI and power-efficiency capabilities for many years with the Snapdragon family of SoCs for mobile, networking and embedded markets. …
RESEARCH PAPER: Qualcomm: A New Force In Cloud AI Read More »
While the global semiconductor industry has matured on many fronts, producing faster, cheaper and more power-efficient devices in vast quantities, lifecycle management for silicon remains lacking. Until now, there has been little thought given to the need for and benefits of an end-to-end, data-centric solution. Hopefully, this situation is about to change. You can download …
RESEARCH PAPER: Comprehensive Silicon Lifecycle Management Read More »
When the only company you can beat is yourself, what do you do? After all, you are the leader, right? And nobody else is even suited up and on the court. Some companies might rest on their laurels, saving money and slowing down R&D. NVIDIA is not one of those companies. Two years ago, the …
Today AMD announced its first data center GPU to compete in high-performance computing (HPC) and Artificial Intelligence (AI). Last year, the company announced that it would bifurcate its GPU technology into two architectures: CDNA for computation and RDNA for graphics. This approach is now coming to fruition and should allow the company to optimize chips …
AMD Goes After NVIDIA With New GPU For The Datacenter Read More »
MLPerf, an industry consortium of over 70 companies and institutions, has released the second round of AI Inference processing results. These benchmarks now represent production applications from all major areas of AI deployment today. But only a few technologies participated in the contest. Many observers and investors expect NVIDIA to encounter more competition in the market for inference accelerators. The hypothesis is that GPUs consume too much energy, are expensive, and cannot …
The 3rd annual AI Hardware Summit concluded last week, after four days of mind-bending presentations, panels and discussions about the Cambrian Explosion in AI. For well over two years, many of us industry observers have waited for the players, big and small, to present working production silicon with benchmarks. In previous years, only NVIDIA delivered (or should …
NVIDIA Co-founder and CEO Jensen Huang rarely disappoints his audience nor his investors. This week he once again delivered the goods at the GPU Technology Conference. Announcing a broad range of hardware and software innovations, Jensen made it clear that he intends to reshape computation, from GPUs to CPUs to NICs and switches. So, let’s …
The explosive growth of AI processing in data center and edge environments has induced AI startups and established firms alike to develop silicon to handle the massive processing demands of neural networks. Inference processing, in particular, is an emerging opportunity, wherein a trained deep neural network is processed to predict characteristics of new data samples. …
RESEARCH PAPER: Tenstorrent’s Holistic Stack Of AI Innovation Read More »
While NVIDIA dominates the market for AI-specific silicon accelerating the training of neural networks, many AI startups are developing silicon to accelerate inference processing, both for data center and edge applications. CPUs have typically been the choice for inference processing, but this is changing rapidly as the size of neural networks grows exponentially and applications …
Last year, Qualcomm teased its Cloud AI100, promising strong performance and power efficiency to enable Artificial Intelligence in cloud edge computing, autonomous vehicles and 5G infrastructure. Today, the company announced it is now sampling the platform, with volume shipments planned for the first half of 2021. This begs the question: why would a company known for …
I often opine that NVIDIA needs a data center-class CPU to compete with Intel and AMD, both of whom have used tightly-coupled CPU/GPU technology to win the first three U.S. exascale supercomputer deals. Connecting massive GPUs to fast CPUs over a painfully slow PCIe interface will not meet the needs of the future of supercomputing …
NVIDIA Needed A CPU, But Did It Need To Buy Arm To Get One? Read More »
Last May, when NVIDIA unveiled the Ampere GPU architecture, the company announced a new supercomputer named Selene that ranks #7 in the world in total performance. Selene is now the fastest industrial system in the USA and is the second-most energy-efficient system ever built. The air-cooled Selene was constructed in a standard data center in …
NVIDIA Provides More Details On Selene Supercomputer Read More »
Last November I covered Blaize and its silicon and software strategy, and noted that the company’s fairly large team has been focused on early customer engagements to gain insights and accelerate adoption. Now the company, backed by industrial heavyweights such as Samsung, Daimler and Denso, is advancing from development into full production and customer deployment. Blaize …
Today, the industry standard AI benchmarking group, mlperf, released its 3rd raft of submissions for training AI networks, and just like the first two releases, NVIDIA swept a sparse competitive field in the category of commercially available hardware and software. Mlperf, comprised of some 80 companies and universities around the world, creates benchmarks to provide …
Graphcore, a UK-based startup, launched its first Intelligence Processing Unit (IPU) for AI acceleration in 2018. Today it introduced its second-generation product for AI, a massively parallel chip with 59.4 billion transistors that delivers some 250 Trillion Operations per Second (TOPS). However, the company’s potential to challenge NVIDIA, the leader in data center AI, lies …
