An Unscented Hound for Working Memory (AUHWM) is a new framework for the real-time tracking of human Working Memory (WM) that can be used to adapt computer interfaces to users' available cognitive resources. WM is the part of human cognition responsible for the short term storing and handling of information; it can, in stressful situations, under information overload or when suffering from dementia-like diseases, become severely limited, possibly leading to poor decision making. Our preliminary results suggest that AUHWM can provide a precise and timely assessment of WM capacity, so that the cognitive load a specific task imposes on users can be adapted, e.g., at the User Interface (UI) level. AUHWM is based on a low-level stochastic discrete model of human WM dynamics, implemented as a Gradient-Boosting-derived deterministic algorithm that simulates users' oblivion. AUHWM also performs Unscented Kalman filtering to track users' WM-specific parameters in real time, thus providing a dynamic assessment of their cognitive resources. Our approach has been tested and validated using data collected from Match$ ^2$s, a visual memory game played by 18 users in another study. Going beyond real-time WM tracking, AUHWM is intended to also be used for WM prediction, paving the way to the adaptation of tasks and their UIs in real time as a function of users' cognitive abilities; we detail an example of such an adapted system, and provide experimental evidence this approach could lead to future enhanced WM-adapted UIs.

We introduce MATCHS (Memory Adaptation Through Cognitive Handling Simulation), a new feature for human-computer interaction (HCI) that enables tasks to be more efficiently performed when they heavily depend on a user's working memory (WM) capacity. WM is the part of human cognition responsible for short-term information storage; it is key to the proper completion of one's current task(s). Known to have very limited capacity and a fast decaying time, in particular with age or when Alzheimer-like diseases set in, WM is one of the strongest factors that explain individual differences in cognitive abilities, thus motivating the introduction of WM specific parameters in personalized user interface design. Our MATCHS framework for HCI design builds upon a low level model of the user's WM to predict how much, and for how long, an information can be expected to be stored there. Thus, the task at hand can, accordingly, be dynamically adjusted. We implemented our approach in a new memory game named Match²s, and tested our framework, including with a small set of users. Our results suggest that MATCHS is able to properly assess someone's current WM characteristics and track its evolution as users' motivation or focus evolve over time, providing useful information to adapt simple interaction scenarii such as the one in Match²s. Future work will include more testing and applications, in particular with users for whom such interfaces could be a major asset, i.e., patients suffering from dementia.

We describe how 2-level memory hierarchies can be exploited to optimize the implementation of teams in the parallel facet of the upcoming Fortran 2015 standard. We focus on reducing the cost associated with moving data within a computing node and between nodes, finding that this distinction is of key importance when looking at performance issues. We introduce a new hardware-aware approach for PGAS, to be used within a runtime system, to optimize the communications in the virtual topologies and clusters that are binding different teams together. We have applied, and implemented into the CAF OpenUH compiler, this methodology to three important collective operations, namely barrier, all-to-all reduction and one-to-all broadcast, this is the first Fortran compiler that both provides teams and handles such a memory hierarchy methodology within teams.

The concept of liquid clocks introduced in this paper is a significant step towards a more precise compile-time framework for the analysis of synchronous and polychromous languages. Compiling languages such as Lustre or Signal indeed involves a number of static analyses of programs before they can be synthesized into executable code, e.g., synchronicity class characterization, clock assignment, static scheduling or causality analysis. These analyses are often equivalent to undecidable problems, necessitating abstracting such programs to provide sound yet incomplete analyses. Such abstractions unfortunately often lead to the rejection of programs that could very well be synthesized into deterministic code, provided abstraction refinement steps could be applied for more accurate analysis. To reduce the number of false negatives occurring during the compilation process, we leverage recent advances in type theory - with the definition of decidable classes of value-dependent type systems - and formal verification, linked to the development of efficient SAT/SMT solvers, to provide a type-theoretic approach that considers all the above analyses as type inference problems. To simplify the exposition of our new approach in this paper, we define a refinement type system for a minimalistic, synchronous, stream-processing language to concisely represent, analyze, and verify logical and quantitative properties of programs expressed as stream-processing data-flow networks. Our type system provides a new framework for representing logical time (clocks) and scheduling properties, and to describe their relations with stream values and, possibly, other quantas. We show how to analyze synchronous stream processing programs (à la Lustre, Signal) to enable previously described analyses involved in compiling such programs. We also prove the soundness of our type system and elaborate on the adaptability of this core framework by outlining its extensibility to specific models of computations and other quantas.

We present qualitative experimental evidence that the "Wiimprovisation" process of using Nintendo Wiimotes as virtual instruments linked to a musical sound system within the framework of Group Music Therapy sessions can provide effective psychodynamic mediation for patients. We designed and implemented specific modalities for movement-based sound control and tested our tool in two clinical settings with children (age 7 to 12) suffering from behavioral disorders. Our preliminary results show immediate acceptance of, long term motivation for and meaningful expression through our system by patients. Future work will focus on assessing the therapeutic potential of our platform's personalization features in a controlled experiment.

Effect systems extend classical type systems with effect inalgorithm is sound and complete w .r.t. the static semantics.

The type and effect discipline, a framework for reconstructing the principal type and the minimal effect of expressions in implicitly typed polymorphic functional languages that support imperative constructs, is introduced. The type and effect discipline outperforms other polymorphic type systems. Just as types abstract collections of concrete values, effects denote imperative operations on regions. Regions abstract sets of possibly aliased memory locations. Effects are used to control type generalization in the presence of imperative constructs while regions delimit observable side effects. The observable effects of an expression range over the regions that are free in its type environment and its type; effects related to local data structures can be discarded during type reconstruction. The type of an expression can be generalized with respect to the variables that are not free in the type environment or in the observable effect.>

Abstract We present a new static system which reconstructs the types, regions and effects of expressions in an implicitly typed functional language that supports imperative operations on reference values. Just as types structurally abstract collections of concrete values, regions represent sets of possibly aliased reference values and effects represent approximations of the imperative behaviour on regions. We introduce a static semantics for inferring types, regions and effects, and prove that it is consistent with respect to the dynamic semantics of the language. We present a reconstruction algorithm that computes the types and effects of expressions, and assigns regions to reference values. We prove the correctness of the reconstruction algorithm with respect to the static semantics. Finally, we discuss potential applications of our system to automatic stack allocation and parallel code generation.

PIPS is an experhnental FORTRAN source-to-source parallelizer that combines the goal of exploring interprocedural and semantical analysis with a requirement for compilation speed.We present in this paper the main features of PIPS, i.e., demand-driven architecture, automatic support for multiple implementation languages, structured control graph, predicates and regions for interprocedural analysis and global nested loop paralle~lzation, with an emphasis on its core data structures and transformation phases.Some preliminary results on the practical impact of our design choices are discussed.

We present the first algorithm for reconstructing the types and effects of expressions in the presence of first class procedures in a polymorphic typed language, Effects are static descriptions of the dynamic behavior of expressions.Just as a type describes what an expression computes, an effect describes howan expression computes.Types are more complicated to reconstruct in the presence of effects because the algebra of effects induces complex constraints on both effects and types.In this paper we show how to perform reconstruction in the presence of such constraints with a new algorithm called algebraic reconstruction, prove that it is sound and complete, and discuss its practical import.

A semantic file system is an information storage system that provides flexible associative access to the system's contents by automatically extracting attributes from files with file type specific transducers. Associative access is provided by a conservative extension to existing tree-structured file system protocols, and by protocols that are designed specifically for content based access. Compatiblity with existing file system protocols is provided by introducing the concept of a virtual directory. Virtual directory names are interpreted as queries, and thus provide flexible associative access to files and directories in a manner compatible with existing software. Rapid attribute-based access to file system contents is implemented by automatic extraction and indexing of key properties of file system objects. The automatic indexing of files and directories is called "semantic" because user programmable transducers use information about the semantics of updated file system objects to extract the properties for indexing. Experimental results from a semantic file system implementation support the thesis that semantic file systems present a more effective storage abstraction than do traditional tree structured file systems for information sharing and command level programming.

Generalized reductions include some of the most well known programming idioms, for instance loop invariant variables, induction variables and reduction operations. We propose a unified framework that allows the detection of these paradigms and thus the efficient parallel implementation of programs that use these otherwise parallel-inhibiting constructs. Moreover, using a semantic-based symbolic evaluator, this technique is able to detect parallelizable constructs inside standard benchmarks that no other vectorizer or parallelizer can currently handle. An interesting by-product of our approach is that correctness proofs can be based on the sound and powerful abstract interpretation theory. This method has been implemented in the Velour vectorizer under current development at the Bull Research Center.

We present a new static analysis method for first-class continuations that uses an effect system to classify the control domain behavior of expressions in a typed polymorphic language. We introduce two new control effects, goto and comefrom, that describe the control flow properties of expressions. An expression that does not have a goto effect is said to be continuation following because it will always call its passed return continuation. An expression that does not have a comefrom effect is said to be continuation discarding because it will never preserve its return continuation for later use. Unobservable control effects can be masked by the effect system. Control effect soundness theorems guarantee that the effects computed statically by the effect system are a conservative approximation of the dynamic behavior of an expression.

The parallelization of sequential programs is an adequate approach for the easy use of architectural features provided on parallel computers. We propose to enhance this technique with the notion of semantic parallelization. The principle is to consider the transformations of programs induced by parallelization as non-standard denotational semantics of the source programming language. We show how to apply this concept to detect, in a toy language ALL, parallelizable complex commands and to deal with some type of programs using indirections. Thanks to results in domain theory and abstract interpretation, we give correctness proofs for these transformations with respect to ALL standard semantic. A byproduct of our approach is that a denotational specification is also an executable prototype ;hence, we were able to implement a semantic parallelizer in the ML functional language. Running examples are supplied.