Section: Overall Objectives

Overall Objectives

Alchemy is a joint Inria/University of Paris Sud research group.

The general research topics of the Alchemy group are architectures, languages and compilers for high-performance embedded and general-purpose processors. Alchemy investigates scalable architecture and compiler/programming solutions for high-performance general-purpose and embedded processors. Alchemy stands for Architectures, Languages and Compilers to Harness the End of Moore Years, referring to both the traditional processor architectures implemented using the current photo-lithographic processes, and novel architecture/language paradigms compatible with future and alternative technologies. The current emphasis of Alchemy is on the former part, and we are progressively increasing our efforts on the latter part.

The research goals of Alchemy span from short term to long term. The short-term goals target existing complex processor architectures, and thus focus on improving program performance on these architectures (software-only techniques). The medium-term goals target the upcoming CMPs (Chip Multi-Processors) with a large number of cores, which will result from the now slower progression of core clock frequency due to technological limitations. The main challenge is to take advantage of the large number of cores for a wide range of applications, considering that automatic parallelization techniques have not yet proved an adequate solution. In Alchemy , we explore joint architecture/programming paradigms as a pragmatic alternative solution. Finally, even longer term research is conducted with the goal of harnessing the properties of future and alternative technologies for processing purposes.

Most of the research in Alchemy attempts to jointly consider the hardware and software aspects, based on the premise that many of the limitations of existing architecture and compiler techniques stem from the lack of cooperation between architects and compiler designers. However, Alchemy addresses the aforementioned research goals through two different, though sometimes complementary, approaches. One approach considers that, in spite of their complexity, architectures and programs can still be accurately and efficiently modeled (and optimized) using analytical methods. The second approach considers the architecture/program pair already has or will reach a complexity level that will evade analytical methods, and explores a complex systems approach; the principle is to accept that the architecture/program pair is more easily understood (and thus optimized) based on its observed behavior rather than inferred from its known design.