Objective: Various types of sensors, such as dynamometers, have been developed to assist in strengthening the pelvic floor muscles, aiming to improve the quality of life for women affected by urinary incontinence. This paper presents silicone encapsulation method for portable vaginal dynamometers that minimizes force measurement drift caused by thermal expansion mismatch between the silicone and the dynamometer housing due to body temperature. Methods: The encapsulation process involves two steps. First, based on the size and shape of the dynamometer, a mold is created to form a cured silicone sleeve slightly larger than the sensor. This sleeve is then slid over the dynamometer. A second silicone layer is subsequently applied over the sleeve and any exposed surfaces of the dynamometer. The dynamometers were tested in air and water at 40 °C to simulate thermal conditions and assess the force measurement drift at body temperature. Results: The proposed method limited the force drift to 0.014 N -a significant reduction compared to the 5 N observed when the silicone was directly applied to the dynamometer surface. This demonstrates the effectiveness of the two-layer encapsulation in mitigating the impact of thermal expansion on the measured force. Significance: This may pave the way to accurate personal pelvic dynamometers for at-home and personalized pelvic muscle training.

Reclaiming cyclic garbage has been a long-standing challenge in automatic memory management. Common approaches to this problem often involve extending reference counting with an asynchronous background task to reclaim cycles. While this ensures that cycles are eventually collected, it also introduces unpredictable behaviours, making these approaches unsuitable for applications where deterministic collection is required.

Dynamic and polymorphic languages attach information, such as types, to run time objects, and therefore adapt the memory layout of values to include space for this information. This makes it difficult to efficiently implement IEEE754 floating-point numbers as this format does not leave an easily accessible space to store type information. The three main floating-point number encodings in use today, tagged pointers, NaN-boxing, and NuN-boxing, have drawbacks. Tagged pointers entail a heap allocation of all float objects, and NaN/NuN-boxing puts additional run time costs on type checks and the handling of other objects. This paper introduces self-tagging, a new approach to object tagging that uses an invertible bitwise transformation to map floating-point numbers to tagged values that contain the correct type information at the correct position in their bit pattern, superimposing both their value and type information in a single machine word. Such a transformation can only map a subset of all floats to correctly typed tagged values, hence self-tagging takes advantage of the non-uniform distribution of floating point numbers used in practice to avoid heap allocation of the most frequently encountered floats. Variants of self-tagging were implemented in two distinct Scheme compilers and evaluated on four microar¬chitectures to assess their performance and compare them to tagged pointers, NaN-boxing, and NuN-boxing. Experiments demonstrate that, in practice, the approach eliminates heap allocation of nearly all floating-point numbers and provides good execution speed of float-intensive benchmarks in Scheme with a negligible performance impact on other benchmarks, making it an attractive alternative to tagged pointers, alongside NaN-boxing and NuN-boxing.

Basic Block Versioning (BBV) is a compilation technique for optimizing program execution. It consists in duplicating and specializing basic blocks of code according to the execution contexts of the blocks, up to a version limit. BBV has been used in Just-In-Time (JIT) compilers for reducing the dynamic type checks of dynamic languages. Our work revisits the BBV technique to adapt it to Ahead-of-Time (AOT) compilation. This Static BBV (SBBV) raises new challenges, most importantly how to ensure the convergence of the algorithm when the specializations of the basic blocks are not based on profiled variable values and how to select the good specialization contexts. SBBV opens new opportunities for more precise optimizations as the compiler can explore multiple versions and only keep those within the version limit that yield better generated code. In this paper, we present the main SBBV algorithm and its use to optimize the dynamic type checks, array bound checks, and mixed-type arithmetic operators often found in dynamic languages. We have implemented SBBV in two AOT compilers for the Scheme programming language that we have used to evaluate the technique’s effectiveness. On a suite of benchmarks, we have observed that even with a low limit of 2 versions, SBBV greatly reduces the number of dynamic type tests (by 54% and 62% on average) and accelerates the execution time (by about 10% on average). Previous work has needed a higher version limit to achieve a similar level of optimization. We also observe a small impact on compilation time and code size (a decrease in some cases).

Software supply chain attacks are increasingly frequent and can be hard to guard against. Reproducible builds ensure that generated artifacts (executable programs) can be reliably created from their source code. However, the tools used by the build process are also vulnerable to supply chain attacks so a complete solution must also include reproducible builds for the various compilers used. With this problem as our main motivation we explore the use of the widely available POSIX shell as the only trusted pre-built binary for the reproducible build process. We have developed pnut, a C to POSIX shell transpiler written in C that generates human-readable shell code. Because the compiler is self-applicable, it is possible to distribute a human-readable shell script implementing a C compiler that depends only on the existence of a POSIX compliant shell such as bash, ksh, zsh, etc. Together, pnut and the shell serve as the seed for a chain of builds that create increasingly capable compilers up to the most recent version of the GNU Compiler Collection (GCC) that is a convenient basis to build any other required tool in the toolchain. The end result is a complete build toolchain built only from a shell and human-readable source files. We discuss the level of C language support needed to achieve our goal, the generation of portable POSIX shell code from C, and the performance of the compiler and generated code.

Python is a popular programming language whose performance is known to be uncompetitive in comparison to static languages such as C. Although significant efforts have already accelerated implementations of the language, more efficient ones are still required. The development of such optimized implementations is nevertheless hampered by its complex semantics and the lack of an official formal semantics. We address this issue by presenting an approach to define an executable semantics targeting the development of optimizing compilers. This executable semantics is written in a format that highlights type checks, primitive values boxing and unboxing, and function calls, which are all known sources of overhead. We also present semPy, a partial evaluator of our executable semantics that can be used to remove redundant operations when evaluating arithmetic operators. Finally, we present Zipi, a Python optimizing compiler prototype developed with the aid of semPy. On some tasks, Zipi displays performance competitive with that of state-of-the-art Python implementations.

Property caches are a well-known technique invented over 30 years ago to improve dynamic object accesses. They have been adapted to JavaScript, which they have greatly contributed to accelerate. However, this technique is applicable only when some constraints are satisfied by the objects, the properties, and the property access sites. In this work, we propose enhancements to improve two common usage patterns: prototype accesses and megamorphic accesses. We have implemented these in the Hopc AOT JavaScript compiler and we have measured their impact. We observe that they effectively complement traditional caches. They reduce cache misses and consequently accelerate execution. Moreover, they do not cause a slowdown in the handling of the other usage patterns.

Function duplication is widely used by JIT compilers to efficiently implement dynamic languages. When the source language supports higher order functions, the called function's identity is not generally known when compiling a call site, thus limiting the use of function duplication. This paper presents a JIT compilation technique enabling function duplication in the presence of higher order functions. Unlike existing techniques, our approach uses dynamic dispatch at call sites instead of relying on a conservative analysis to discover function identity. We have implemented the technique in a JIT compiler for Scheme. Experiments show that it is efficient at removing type checks, allowing the removal of almost all the run time type checks for several benchmarks. This allows the compiler to generate code up to 50% faster. We show that the technique can be used to duplicate functions using other run time information opening up new applications such as register allocation based duplication and aggressive inlining.

Previous work proposed lazy basic block versioning, a technique for just-in-time compilation of dynamic languages which we believe represents an interesting point in the design space. Basic block versioning is simple to implement, simple enough that a single developer can build a complete just-in-time compiler for JavaScript in a year, yet it performs surprisingly well as it propagates context-sensitive type information to generate type-specialized code on the fly. In this paper, we demonstrate that lazy basic block versioning can be extended is simple ways to propagate type information across function call boundaries. This gives some of the benefits of whole-program analysis, or a tracing compiler, without having to implement the machinery for either. We have implemented this proposal in the Higgs JavaScript virtual machine and report on the empirical evaluation of this system on a set of industry standard benchmarks. The approach eliminates 94.3 of dynamic type tests on average, which we show is more than what is achievable with any static whole-program type analysis.

Task migration allows a running program to continue its execution in a different destination environment. Increasingly, execution environments are defined by combinations of cultural and technological constraints, affecting the choice of host language, libraries and tools. A compiler supporting multiple target environments and task migration must be able to marshal continuations and then unmarshal and continue their execution, ideally, even if the language of the destination environment is different. In this paper, we propose a compilation approach based on a virtual machine that strikes a balance between implementation portability and efficiency. We explain its implementation within a Scheme compiler targeting JavaScript, PHP, Python, Ruby and Java -- some of the most popular host languages for web applications. As our experiments show, this approach compares well with other Scheme compilers targeting high-level languages in terms of execution speed, being sometimes up to 3 orders of magnitude faster.

Dynamically typed programming languages such as JavaScript and Python defer type checking to run time. In order to maximize performance, dynamic language VM implementations must attempt to eliminate redundant dynamic type checks. However, type inference analyses are often costly and involve tradeoffs between compilation time and resulting precision. This has lead to the creation of increasingly complex multi-tiered VM architectures. This paper introduces lazy basic block versioning, a simple JIT compilation technique which effectively removes redundant type checks from critical code paths. This novel approach lazily generates type-specialized versions of basic blocks on-the-fly while propagating context-dependent type information. This does not require the use of costly program analyses, is not restricted by the precision limitations of traditional type analyses and avoids the implementation complexity of speculative optimization techniques. We have implemented intraprocedural lazy basic block versioning in a JavaScript JIT compiler. This approach is compared with a classical flow-based type analysis. Lazy basic block versioning performs as well or better on all benchmarks. On average, 71% of type tests are eliminated, yielding speedups of up to 50%. We also show that our implementation generates more efficient machine code than TraceMonkey, a tracing JIT compiler for JavaScript, on several benchmarks. The combination of implementation simplicity, low algorithmic complexity and good run time performance makes basic block versioning attractive for baseline JIT compilers.

JavaScript is one of the most widely used dynamic languages. The performance of existing JavaScript VMs, however, is lower than that of VMs for static languages. There is a need for a research VM to easily explore new implementation approaches. This paper presents the Tachyon JavaScript VM which was designed to be flexible and to allow experimenting with new approaches for the execution of JavaScript. The Tachyon VM is itself implemented in JavaScript and currently supports a subset of the full language that is sufficient to bootstrap itself. The paper discusses the architecture of the system and in particular the bootstrapping of a self-hosted VM. Preliminary performance results indicate that our VM, with few optimizations, can already execute code faster than a commercial JavaScript interpreter on some benchmarks.

Just-In-Time (JIT) compilation is frequently used in software engineering to accelerate program execution. Parts of the code are translated to machine code at runtime to speedup their execution by exploiting local and dynamic information of the computation. Modern FPGAs manufactured by Xilinx allow partial and dynamic configuration. Such features make them eligible platforms for JIT hardware compilation. Nevertheless, this has not been achieved until now because the mapping between a bitstream and the programmable points inside these FPGAs is not documented. In this article, we propose a methodology to retrieve the relevant information in logarithmic time per bit by methodically using the tools distributed by Xilinx. We give a practical case study which details the analysis of a Virtex-II Pro FPGA bitstream. The mapping of CLBs, BRAMs, and multipliers has been fully determined. Thanks to this information, we have been able to prototype tools in the fields of reverse mapping FPGA bitstreams, low-level simulation, and custom place-and-route. Finally preliminary results demonstrate that a processor embedded in an FPGA can compile, place, and route arithmetic and logic expressions inside the FPGA within a few milliseconds.

Compilers for dynamically and statically typed languages ensure safe execution by verifying that all operations are performed on appropriate values. An operation as simple as car in Scheme and hd in SML will include a run time check unless the compiler can prove that the argument is always a non-empty list using some type analysis. We present a demand-driven type analysis that can adapt the precision of the analysis to various parts of the program being compiled. This approach has the advantage that the analysis effort can be spent where it is justified by the possibility of removing a run time check, and where added precision is needed to accurately analyze complex parts of the program. Like the k-cfa our approach is based on abstract interpretation but it can analyze some important programs more accurately than the k-cfa for any value of k. We have built a prototype of our type analysis and tested it on various programs with higher order functions. It can remove all run time type checks in some nontrivial programs which use map and the Y combinator.

We present a new near-real-time compacting collector and its implementation in a production quality Scheme compiler (Gambit-C). Our goal is to use this system as a base for an implementation of Erlang for writing soft real-time telecommunication applications. We start with a description of Gambit-C's memory organisation and its blocking collector. The design and integration of the incremental collector within Gambit-C are then explained. Finally we measure the performance of the incremental collector and compare it to the original blocking collector. We found that the overhead of the incremental collector is high (a factor of 1.3 to 8.1, with a median of 2.24) but nevertheless the collection pauses are compatible with typical soft real-time requirements (we get an average pause of 2.9 milliseconds and a maximum pause of 15 milliseconds on a 133Mhz DEC Alpha 21064).

In this paper we present a new program analysis method which we call Storage Use Analysis. This analysis deduces how objects are used by the program and allows the optimization of their allocation. This analysis can be applied to both statically typed languages (e.g. ML) and latently typed languages (e.g. Scheme). It handles side-effects, higher order functions, separate compilation and does not require CPS transformation. We show the application of our analysis to two important optimizations: stack allocation and unboxing. The first optimization replaces some heap allocations by stack allocations for user and system data storage (e.g. lists, vectors, procedures). The second optimization avoids boxing some objects. This analysis and associated optimitations have been implemented in the Bigloo Scheme/ML compiler. Experimental results show that for many allocation intensive programs we get a significant speedup. In particular, numerically intensive programs are almost 20 times faster because floating point numbers are unboxed and no longer heap allocated.

Abstract Over 25 implementations of different functional languages are benchmarked using the same program, a floating-point intensive application taken from molecular biology. The principal aspects studied are compile time and execution time for the various implementations that were benchmarked. An important consideration is how the program can be modified and tuned to obtain maximal performance on each language implementation. With few exceptions, the compilers take a significant amount of time to compile this program, though most compilers were faster than the then current GNU C compiler (GCC version 2.5.8). Compilers that generate C or Lisp are often slower than those that generate native code directly: the cost of compiling the intermediate form is normally a large fraction of the total compilation time. There is no clear distinction between the runtime performance of eager and lazy implementations when appropriate annotations are used: lazy implementations have clearly come of age when it comes to implementing largely strict applications, such as the Pseudoknot program. The speed of C can be approached by some implementations, but to achieve this performance, special measures such as strictness annotations are required by non-strict implementations. The benchmark results have to be interpreted with care. Firstly, a benchmark based on a single program cannot cover a wide spectrum of ‘typical’ applications. Secondly, the compilers vary in the kind and level of optimisations offered, so the effort required to obtain an optimal version of the program is similarly varied.