One of the main objectives of the TANGO Project is to be able to optimize energy usage of applications in an heterogeneous environment –where by heterogeneous we are understating a mixture of different processor devices, such as CPUs, GPUs, FPGAs, DSPs, and so on.- One of the main challenges is to be able to monitor energy usage of those devices without the necessity of intrusive measurements, such as adding over the top physical probes.
During the last decade the software and computing industry has lived a revolutionary change that deeply impacts on how developers embark on delivering software. The mainstream computing landscape has shifted from single–processor machines, to a multi-core, multi-type machines. This “multi-everything” trend has changed all types of computers, devices (phones, tablets, IoT devices and sensors) plus the option of also using remote cloud infrastructures, also providing heterogeneity.
The current computing ecosystem is becoming more and more heterogeneous. On the one hand, trends in computer architectures focuses on providing different computing devices (CPUs, GPUs and FPGAs) and memories in a single chip or computing node, with the aim of providing better computing devices for the different types of algorithms and applications.
“In the twilight of Moore’s Law, the transitions to multicore processors, GPU computing, and HaaS cloud computing are not separate trends, but aspects of a single trend – mainstream computers from desktops to ‘smartphones’ are being permanently transformed into heterogeneous supercomputer clusters. Henceforth, a single compute-intensive application will need to harness different kinds of cores, in immense numbers, to get its job done.
The free lunch is over. Now welcome to the hardware jungle.”