If an Inference IP supplier or Inference Accelerator Chip supplier offers a benchmark, it is probably ResNet-50. As a result, it might seem logical to use ResNet-50 to compare inference offerings. If ...
Much has been written about the computational complexity of inference acceleration: very large matrix multiplies for fully-connected layers and huge numbers of 3×3 convolutions across megapixel images ...
Nvidia has claimed performance records with its AI computing platform in the latest round of MLPerf AI inference benchmarks. MLPerf is the industry’s independent benchmark consortium that measures AI ...
Today AI chip startup Groq announced that their new Tensor processor has achieved 21,700 inferences per second (IPS) for ResNet-50 v2 inference. Groq’s level of inference performance exceeds that of ...
A few months back, I wrote about the MLPerf consortium and the release of its Inference v0.5 benchmark. MLPerf had previously disclosed some performance results from its Training v0.6 benchmark, but ...
Silicon Valley-based startup Mipsology announced today that its Zebra AI inference accelerator achieved the highest efficiency based on the MLPerf inference test. The benchmark, which measures ...
It’s important to understand that an inference accelerator is a completely new kind of chip, with many unknowns for the broader market. In our industry, there’s a learning curve for everything, from ...
There is much at stake in the world of datacenter inference and while the market has not yet decided its winners, there are finally some new metrics in the bucket to aid decision-making. Interpreting ...
While AI training dims the lights at hyperscalers and cloud builders and costs billions of dollars a year, in the long run, there will be a whole lot more aggregate processing done on AI inference ...
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