high-performance computing
Exploring energy efficiency
Mirren White explains how a European project to
understand and improve energy efficiency in HPC and embedded computing is creating tools that can be used to design more efficient HPC systems
E
nergy efficiency is one of the key challenges of modern computing – in an era where even the most efficient supercomputers come with
massive energy bills, technology that can help to increase energy efficiency is critical to sustainable HPC development. Te problem, of course, is performance.
Today, the most power-efficient supercomputers are not the most powerful; the best and most powerful systems are not the most power-efficient. Shoubu, the current leader of the Green500, only just breaks into the top 100 most powerful supercomputers in the world at #94 (as of June 2016). Meanwhile, the most powerful supercomputer in the world, China’s Sunway TaihuLight (as of June 2016) has a vastly superior Rmax value (1 petaFLOP vs 93 petaFLOPs) but consumes almost 30 times as much power as Shoubu (0.55 MW vs 15.4 MW). Clearly, the balance of power and
performance is a key issue. As we move towards the exascale era of high- performance computing, a significant step forward in power efficiency will be necessary – even for today’s most efficient systems. Tis is where Adept enters the frame.
A three-year, European project funded under the European Commission’s Seventh Framework initiative, Adept’s sole focus is
8 SCIENTIFIC COMPUTING WORLD
Adept’s power measurement system
on understanding and improving energy efficiency in both high-performance and embedded computing. Despite being distinct fields, in the efficiency area both have a similar goal: high performance for low power and energy usage. HPC developers excel at exploiting parallelism for increased performance, while embedded engineers’ fixed energy budgets mean they are experts at balancing performance with power usage. Starting in September 2013, the
major threads of the project have been exploring the implications of parallelism in programming, and investigating the users’ choice of hardware. With this data, we have
EFFICIENT DESIGN OF EFFICIENT SYSTEMS – THIS IS THE ULTIMATE GOAL
been working on developing a number of tools that enable users to quantify power and performance in both soſtware and hardware, and then design a more efficient system. We can also utilise the tools to predict the performance of a piece of soſtware on a system that may not be available or does not yet exist – the aim is to take the guesswork away from novel system design. Te tools suite has three major
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