For the last few years, Graphcore has primarily been focused on slinging its IPU chips for training and inference systems of varying sizes, but that is changing now as the six-year-old British chip designer is joining the conversation about the convergence of AI and high-performance computing. …
The 3D stacking of chips has been the subject of much speculation and innovation in the past decade, and we will be the first to admit that we have been mostly thinking about this as a way to cram more capacity into a given compute engine while at the same time getting components closer together along the Z axis and not just working in 2D anymore down on the X and Y axes. …
When it comes to a silicon startup bringing a product to market in a tough competitive landscape, nothing is easy. …
While securing the high-end particle physics market segment is not likely to push any of the AI/ML ASICS into competition with GPUs anytime soon, the chipmakers that can prove their value on some of the most demanding, real-time AI workloads can capture some serious mindshare. …
…With performance comparable to the Nvidia V100 GPU, a common accelerator in HPC but better energy consumption numbers and memory bandwidth potential, Graphcore can turn heads in supercomputing.
Sponsored by Graphcore
27th January 2021 – 16:00 GMT, 8:00 PT, 11:00 ET
IPU-POD is Graphcore’s unique scale-out solution for high-performance machine intelligence compute, ideal for experimentation to prototype to production systems from IPU-M2000 with 4 IPUs up to supercomputing scale. …
Sponsored by Graphcore
Graphcore, the U.K.-based startup that launched the Intelligence Processing Unit (IPU) for AI acceleration in 2018, has introduced the IPU-Machine. …
There has been a great deal of interest in deep learning chip startup, Graphcore, since we first got the limited technical details of the company’s first-generation chip last year, which was followed by revelations about how their custom software stack can run a range of convolutional, recurrent, generative adversarial neural network jobs. …
The last two years have delivered a new wave of deep learning architectures designed specifically for tackling both training and inference sides of neural networks. …
As a thought exercise, let’s consider neural networks as massive graphs and begin considering the CPU as a passive slave to some higher order processor—one that can sling itself across multiple points on an ever-expanding network of connections feeding into itself, training, inferencing, and splitting off into multiple models on the same architecture. …
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