Section: Research Program

Motivation

Our research program is naturally driven by the evolution of our ecosystem. Relevant recent changes can be classified in the following categories: technological constraints, evolving community, and domain constraints. We hereby summarize these evolutions.

Technological constraints

Until recently, binary compatibility guaranteed portability of programs, while increased clock frequency and improved micro-architecture provided increased performance. However, in the last decade, advances in technology and micro-architecture started translating into more parallelism instead. Technology roadmaps even predict the feasibility of thousands of cores on a chip by 2020. Hundreds are already commercially available. Since the vast majority of applications are still sequential, or contain significant sequential sections, such a trend put an end to the automatic performance improvement enjoyed by developers and users. Many research groups consequently focused on parallel architectures and compiling for parallelism.

The focus of ALF – and the DAL ERC – was paradoxically on Amdahl's law: the performance of applications will ultimately be driven by the performance of the sequential part. Despite a number of advances (some of them contributed by ALF), sequential tasks are still a major performance bottleneck. Addressing it is still on the agenda of the proposed PACAP project-team.

In addition, due to power constraints, only part of the billions of transistors of a microprocessor can be operated at any given time (the dark silicon paradigm). A sensible approach consists in specializing parts of the silicon area to provide dedicated accelerators (not run simultaneously). This results in diverse and heterogeneous processor cores. Application and compiler designers are now confronted with a moving target, challenging portability and jeopardizing performance.

Finally, we live in a world where billions of sensors, actuators, and computers play a crucial role in our life: flight control, nuclear plant management, defense systems, banking, or health care. These systems must be reliable, despite the fact that they are subject to faults (for example due to aging, charged particle hit, or random noise). Faults will soon become the new de facto standard. The evolutions of the semiconductor industry predict an exponential growth of the number of permanent faults [58]. Reliability considerations usually degrade performance. We will propose solutions to mitigate this impact (for example by limiting overheads to critical sections).

Note on technology.

Technology also progresses at a fast pace. We do not propose to pursue any research on technology per se. Recently proposed paradigms (quantum computing, non-Si, brain-inspired) have received lots of attention from the research community. We do not intend to invest in those paradigms, but we will continue to investigate compilation and architecture for more conventional programming paradigms. Still, several technological shifts may have consequences for us, and we will closely monitor their developments, they include for example non-volatile memory (impacts security, makes writes longer than loads), 3D-stacking (impacts bandwidth), and photonics (impacts latencies and connection network).

Evolving community

The PACAP project-team will tackle performance-related issues, for conventional programming paradigms. In fact, programming complex environments is no longer reserved to experts in compilation and architecture. A large community now develops applications for a wide range of targets, including mobile “apps”, cloud, multicore or heterogeneous processors.

This also includes domain scientists (in biology, medicine, but also social sciences) who started relying heavily on computational resources, gathering huge amounts of data, and requiring considerable amount of processing to analyze them. Our research is motivated by the growing discrepancy between on the one hand the complexity of the workloads and the computing systems, and on the other hand the expanding community of developers at large, with limited expertise to optimize and to map efficiently computations to compute nodes.

Domain constraints

Mobile, embedded systems have become ubiquitous. Many of them have real-time constraints. For this class of systems, correctness implies not only producing the correct result, but also doing so within specified deadlines. In the presence of heterogeneous, complex and highly dynamic systems, producing tight (i.e. useful) upper bound to the worst-case execution time has become extremely challenging. Our research will aim at improving the tightness as well as enlarging the set of features that can be safely analyzed.

The ever growing dependence of our economy on computing systems also implies that security has become of utmost importance. Many systems are under constant attacks from intruders. Protection has a cost also in terms of performance. We plan to leverage our background to contribute solutions that minimize this impact.

Note on Applications Domains.

As was already the case for ALF, PACAP will work on fundamental technologies for computer science: processor architecture, performance-oriented compilation and guaranteed response time for real-time. The research results may have impacts on any application domain that requires high performance execution (telecommunication, multimedia, biology, health, engineering, environment...), but also on many embedded applications that exhibit other constraints such as power consumption, code size and guaranteed response time.

We strive to extract from active domains the fundamental characteristics that are relevant to our research. For example, big data is of interest to PACAP because it relates to the study of hardware/software mechanisms to efficiently transfer huge amounts of data to the computing nodes. Similarly, the Internet of Things is of interest because it has implications in terms of ultra low power consumption.