tag: Nvidia

System Bits: Dec. 5
By Ann Mutschler - 05 Dec, 2017 - Comments: 0

[caption id="attachment_429586" align="aligncenter" width="300"] Vivienne Sze, an associate professor of electrical engineering and computer science at MIT. Source: MIT[/caption] Building deep learning hardware A new course at MIT is bringing together both electrical engineering and computer science to educate student in the highly sought after field of deep learning. Vivienne Sze, an assoc... » read more

The New Road Warriors
By Jeff Dorsch - 27 Nov, 2017 - Comments: 0

Chip vendors and other companies that have little or no experience in automotive are flooding into this market as the race for assisted and autonomous driving begins to heat up. This market is expected to pay big dividends for companies that succeed in helping to build the vehicles of the future in this century. IC Insights earlier this year forecast the auto chip market would grow 22% this ... » read more

The Week In Review: Manufacturing
By Mark LaPedus - 17 Nov, 2017 - Comments: 0

Market research For some time, DRAM shortages have plagued the market. Today, the situation remains the same. DRAMs are seeing strong demand. But yet, vendors are not adding any capacity. “Strained DRAM supply was even more evident during the third quarter as limited production capacity and limited technological progress for the memory industry encountered robust demand from data centers in ... » read more

The Next Phase Of Machine Learning
By Kevin Fogarty - 09 Nov, 2017 - Comments: 0

Machine learning is all about doing complex calculations on huge volumes of data with increasing efficiency, and with a growing stockpile of success stories it has rapidly evolved from a rather obscure computer science concept into the go-to method for everything from facial recognition technology to autonomous cars. [getkc id="305" kc_name="Machine learning"] can apply to every corporate fu... » read more

Full-Chip Power Integrity And Reliability Signoff
By Annapoorna Krishnaswamy - 09 Nov, 2017 - Comments: 0

As designs increase in complexity to cater to the insatiable need for more compute power — which is being driven by different AI applications ranging from data centers to self-driving cars—designers are constantly faced with the challenge of meeting the elusive power, performance and area (PPA) targets. PPA over-design has repercussions resulting in increased product cost as well as pote... » read more

Blog Review: Nov. 8
By Jesse Allen - 08 Nov, 2017 - Comments: 0

Synopsys' Eric Huang digs in to what's new with USB 3.2 and what's achieved by preserving the existing PHY signaling speeds. In a video, Mentor's Colin Walls provides tips on how to write debuggable and maintainable embedded code. Cadence's Paul McLellan listens in on a talk by Andrew Kahng of UC San Diego on the problem of scaling and why machine learning can improve EDA tools. Rambus... » read more

Blog Review: Nov. 1
By Jesse Allen - 01 Nov, 2017 - Comments: 0

Mentor's Nitin Bhagwath continues digging into DDR timing with a look at the clock-to-DQS requirement at the DRAM and how "write-leveling" is used to solve layout issues caused by the requirement. Synopsys' Dipesh Handa checks out what's new in the MIPI CSI-2 v2.0 specification that opens it up to new imaging and vision applications, including IoT and automotive. Cadence's Ken Willis delv... » read more

Making Machine Learning Portable
By Ed Sperling - 26 Oct, 2017 - Comments: 0

Machine learning is everywhere, and it has exploded at a pace no one would have expected. Even a year ago, ML was more of an experiment than a reality. NVIDIA's stock price (Fig. 1, below) is a good representation of just how quickly this market has grown. GPUs are the chip of choice for training machine learning systems. Fig. 1: Nvidia 5-year stock price. Source: Google Finance Ma... » read more

Blog Review: Oct. 11
By Jesse Allen - 11 Oct, 2017 - Comments: 0

Mentor's Matthew Balance examines the separation of concerns between test intent and test realization in the Portable Stimulus specification. Synopsys' Deepak Nagaria checks out the features that makes LPDDR4 efficient in terms of power consumption, bandwidth utilization, data integrity and performance. Cadence's Meera Collier listens in as Chris Rowen considers whether AI processing shou... » read more

Toward System-Level Test
By Ed Sperling - 09 Oct, 2017 - Comments: 0

The push toward more complex integration in chips, advanced packaging, and the use of those chips for new applications is turning the test world upside down. Most people think of test as a single operation that is performed during manufacturing. In reality it is a portfolio of separate operations, and the number of tests required is growing as designs become more heterogeneous and as they ar... » read more

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