A combination of Lenovo HPC and system optimization could help genomics detect and defuse healthcare timebombs
Sponsored Feature The concept of precision medicine is revolutionizing healthcare by ‘personalizing’ treatment using genomics to provide insights into a patient’s genetic make-up gleaned from study of their own DNA. …
China is the world’s second largest economy, it has the world’s largest population, and it is only a matter of time before has a world-class technology ecosystem spanning the smallest transistors to the largest hyperscale and HPC systems. …
It was absolutely inevitable that China would try to create its own GPU compute engines. …
In modern system architecture, there is a lot of shifting pieces of systems software (particularly in the control plane) and often their workloads around between pieces of silicon to get better bang for the buck, to improve the overall security of the system, or both. …
If you are an HPC center in Europe, and particularly one that is funded by public funds, you are thinking about Arm-based CPUs in your supercomputers. …
In Nvidia’s decade and a half push to make GPU acceleration core to all kinds of high performance computing, a key component has been the CUDA parallel computing platform that made it easier for developers to create applications that can leverage graphics chips for general purpose processing. …
The “Cirrus” Power10 processor from IBM, which we codenamed for Big Blue because it refused to do it publicly and because we understand the value of a synonym here at The Next Platform, shipped last September in the “Denali” Power E1080 big iron NUMA machine. …
The people running Google Cloud can see the tides of HPC changing and know that, as we discussed only a few months ago, there is a fairly good chance that more HPC workloads will move to cloud builders over time as their sheer scale increasingly dictates future chip and system designs and the economics of processing. …
There is no denying that GPUs have incredible potential to accelerate workloads of all kinds, but developing applications that can scale across two, four, or even more GPUs continues to be a prohibitively expensive proposition. …
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. …
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