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Published on November 3, 2022 by rheocube

As part of delivering cloud based experimentation to R&D departments worldwide, RheoCube is extending its implementation to support AWS Graviton3 ARM chips. This will help RheoCube in its mission to bring the power of data visualization to experimental scientists in a more efficient way. Another key benefit, and a strong rationale for this project, is the capacity for lower emissions. This is made possible by using AWS ARM, and it helps to reduce the environmental impact of data visualization. 


With billions of transistors and specialized subsystems operating at extreme speeds, processors remain some of the most complex devices ever produced. These processors power the detailed computations that R&D departments need to get insights on the materials in their products.

Less energy usage
For RheoCube, a key factor in opting to use AWS ARM was to tap into greener consumption models, that result in less energy usage. This technology was selected to not only deliver faster results, but to do so with less impact on the environment.


Studies by 451 Research have shown that AWS’ infrastructure is 3.6 times more energy efficient than average U.S. enterprise data centers and up to five times more energy efficient than the average in Europe. This research also found that AWS can lower customers’ workload carbon footprints by nearly 80%.


Lower emissions

ARM utilizes specialized processing, with purpose-built CPUs, GPUs, DPUs, and other smart processors that optimally allocate workloads. With workloads spread over multiple processors, results are obtained faster, while running times are dramatically reduced. By leveraging these AWS ARM capabilities, RheoCube can help clients to gain crucial insights on the complex fluids in their products, discover the winning prototypes, and get to market quickly.


In addition, Graviton3 chips are expected to use up to 60% less power, so are significantly better when it comes to reducing the environmental impact of digital research. This helps to ensure that data visualization happens not only faster, but with less consumption of energy resources.


Less waste, faster results

Energy savings aside, researchers also reduce the amount of chemicals they need to use in wet lab experiments. By testing hypotheses and exploring their formulations in RheoCube, scientists can reduce the number of physical lab tests, and thus the amount of expensive chemicals used in R&D.


All of this helps to move wet lab experimentation over to a more sustainable way of working, by providing a way to optimize performance and efficiency while reducing power usage, emissions, and cost.