Pros, Cons Of ML-Specific Chips


Semiconductor Engineering sat down with Rob Aitken, an Arm fellow; Raik Brinkmann, CEO of OneSpin Solutions; Patrick Soheili, vice president of business and corporate development at eSilicon; and Chris Rowen, CEO of Babblelabs. What follows are excerpts of that conversation. To view part one, click here. Part two is here. SE: Is the industry's knowledge of machine learning keeping up with th... » read more

Where ML Works Best


Anirudh Devgan, president of Cadence, sat down with Semiconductor Engineering to discuss machine learning inside and outside of EDA tools and how that will affect the future of chip and system design. What follows are excerpts of that discussion. SE: How do you see the market and use of machine learning shaping up? Devgan: There are three main areas—machine learning inside, machine lear... » read more

Verifying AI, Machine Learning


[getperson id="11306" comment="Raik Brinkmann"], president and CEO of [getentity id="22395" e_name="OneSpin Solutions"], sat down to talk about artificial intelligence, machine learning, and neuromorphic chips. What follows are excerpts of that conversation. SE: What's changing in [getkc id="305" kc_name="machine learning"]? Brinkmann: There’s a real push toward computing at the edge. ... » read more

The Limits Of IP Reuse


The basic business proposition for third-party IP is that it's cheaper, faster, and less problematic to buy rather than build. But things haven't exactly worked out according to plan, either for companies that license IP or those that develop it. For [getkc id="43" kc_name="IP"] licensees, just keeping track of an endless series of updates is becoming unwieldy. Complex designs often include ... » read more

ARC HS4x And HS4xD CPUs


Synopsys’ DesignWare ARC CPUs comprise a family of highly configurable and customizable processor cores, which ship in nearly two billion chips per year. ARC’s popularity in embedded devices makes the company second only to ARM in the number of chips that integrate its licensable CPUs. More than 230 ARC licensees use the cores in products that span a broad range of embedded applications, su... » read more

Supporting CPUs Plus FPGAs


While it has been possible to pair a CPU and FPGA for quite some time, two things have changed recently. First, the industry has reduced the latency of the connection between them and second, we now appear to have the killer app for this combination. Semiconductor Engineering sat down to discuss these changes and the state of the tool chain to support this combination, with Kent Orthner, system... » read more

What Does An AI Chip Look Like?


Depending upon your point of reference, artificial intelligence will be the next big thing or it will play a major role in all of the next big things. This explains the frenzy of activity in this sector over the past 18 months. Big companies are paying billions of dollars to acquire startup companies, and even more for R&D. In addition, governments around the globe are pouring additional... » read more

Homogeneous And Heterogeneous Computing Collide


Eleven years ago processors stopped scaling due to diminishing returns and the breakdown of [getkc id="213" kc_name="Dennard's Law"]. That set in motion a chain of events from which the industry has still not fully recovered. The transition to homogeneous multi-core processing presented the software side with a problem that they did not know how to solve, namely how to optimize the usage of ... » read more

GPU Accelerated Computing


The computing applications used in semiconductor design and manufacturing have ever-increasing requirements for speed, accuracy and reliability. The continuation of Moore's Law creates a perpetual demand for greater accuracy as, with each new process node, larger numbers of increasingly smaller features are crowded onto each mask and wafer. Computing farms, where thousands of central processing... » read more

GPUs Power Ahead


GPUs, long a sideshow for CPUs, are suddenly the rising stars of the processor world. They are a first choice in everything from artificial intelligence systems to automotive ADAS applications and deep learning systems powered by [getkc id="261" kc_name="convolutional neural network"]. And they are still the mainstays of high-performance computing, gaming and scientific computation, to name ... » read more

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