Benzo: Reflective Glue for Low-level Programming

International audienceThe goal of high-level low-level programming is to bring the abstraction capabilities of high-level languages to the system programming domain, such as virtual machines (VMs) and language runtimes. However, existing solutions are bound to compilation time and expose limited possibilities to be changed at runtime and from language-side. They do not fit well with fully reflective languages and environments. We propose Benzo1, a lightweight framework for high- level low-level programming that allows developers to generate and execute at runtime low-level code (assembly). It promotes the implementation, and dynamic modification, of system components with high-level language tools outperforming existing dynamic solutions. Since Benzo is a general framework we choose three applications that cover an important range of the spectrum of system programming for validating the infrastructure: a For- eign Function Interface (FFI), primitives instrumentation and a just-in-time bytecode compiler (JIT). With Benzo we show that these typical VM-level components are feasible as reflective language-side implementations. Due to its unique combination of high-level reflection and low-level programming, Benzo shows better performance for these three applications than the comparable high-level implementations

Waterfall: Primitives Generation on the Fly

Modern languages are typically supported by managed runtimes (Virtual Machines). Since VMs have to deal with many concepts such as memory management, abstract execution model and scheduling, they tend to be very complex. Additionally, VMs have to meet strong performance requirements. This demand of performance is one of the main reasons why many VMs are built statically. Thus, design decisions are frozen at compile time preventing changes at runtime. One clear example is the impossibility to dynamically adapt or change primitives of the VM once it has been compiled. In this work we present a toolchain that allows for altering and configuring components such as primitives and plug-ins at runtime. The main contribution is Waterfall, a dynamic and reflective translator from Slang, a restricted subset of Smalltalk, to native code. Waterfall generates primitives on demand and executes them on the fly. We validate our approach by implementing dynamic primitive modification and runtime customization of VM plug-ins

A Metaobject Protocol for Optimizing Application-Specific Run-Time Variability

Just-in-time compilers and their aggressive speculative optimizations reduced the performance gap between dynamic and static languages drastically. To successfully speculate, compilers rely on the program variability observed at run time to be low, and use heuristics to determine when optimization is beneficial. However, some variability patterns are hard to capture with heuristics. Specifically, ephemeral, warmup, rare, and highly indirect variability are challenges for today's compiler heuristics. As a consequence, they can lead to reduced application performance. However, these types of variability are identifiable at the application level and could be mitigated with information provided by developers. As a solution, we propose a metaobject protocol for dynamic compilation systems to enable application developers to provide such information at run time. As a proof of concept, we demonstrate performance improvements for a few scenarios in a dynamic language built on top of the Truffle and Graal system

Building Efficient and Highly Run-time Adaptable Virtual Machines

Programming language virtual machines (VMs) realize language semantics, enforce security properties, and execute applications efficiently. Fully Reflective Execution Environments (EEs) are VMs that additionally expose their whole structure and behavior to applications. This enables developers to observe and adapt VMs at run time. However, there is a belief that reflective EEs are not viable for practical usages because such flexibility would incur a high performance overhead. To refute this belief, we built a reflective EE on top of a highly optimizing dynamic compiler. We introduced a new optimization model that, based on the conjecture that variability of low-level (EE-level) reflective behavior is low in many scenarios, mitigates the most significant sources of the performance overheads related to the reflective capabilities in the EE. Our experiments indicate that reflective EEs can reach peak performance in the order of standard VMs. Concretely, that a) if reflective mechanisms are not used the execution overhead is negligible compared to standard VMs, b) VM operations can be redefined at language-level without incurring in significant overheads, c) for several software adaptation tasks, applying the reflection at the VM level is not only lightweight in terms of engineering effort, but also competitive in terms of performance in comparison to other ad-hoc solutions

Fully-reflective VMs for Ruling Software Adaptation

It has become common for software systems to require or benefit from dynamic adaptation, i.e., to modify their behavior while they are running. Among the existing approaches to this problem, language-level solutions are appealing for scenarios in which fine-grained adaptation is needed, i.e., when the granularity of the modifications is that of individual objects, or for small applications where an architectural solution based on complex middleware is overkill. However, there is no consensus on which of the existing language-level approaches to adopt. A recent survey on self-adaptive systems asks 9: Is it possible to adopt a single paradigm providing all required abstractions to implement adaptive systems

R Melts Brains -- An IR for First-Class Environments and Lazy Effectful Arguments

The R programming language combines a number of features considered hard to analyze and implement efficiently: dynamic typing, reflection, lazy evaluation, vectorized primitive types, first-class closures, and extensive use of native code. Additionally, variable scopes are reified at runtime as first-class environments. The combination of these features renders most static program analysis techniques impractical, and thus, compiler optimizations based on them ineffective. We present our work on PIR, an intermediate representation with explicit support for first-class environments and effectful lazy evaluation. We describe two dataflow analyses on PIR: the first enables reasoning about variables and their environments, and the second infers where arguments are evaluated. Leveraging their results, we show how to elide environment creation and inline functions

Towards Fully Reflective Environments

Modern development environments promote live programming (LP) mechanisms because it enhances the development experience by providing instantaneous feed- back and interaction with live objects. LP is typically supported with advanced reflective techniques within dynamic languages. These languages run on top of Virtual Machines (VMs) that are built in a static manner so that most of their components are bound at compile time. As a consequence, VM developers are forced to work using the traditional edit-compile-run cycle, even when they are designing LP-supporting environments. In this paper we explore the idea of bringing LP techniques to the VM domain for improving their observability, evolution and adaptability at run-time. We define the notion of fully reflective execution environments (EEs), systems that provide reflection not only at the application level but also at the level of the VM. We characterize such systems, propose a design, and present Mate v1, a prototypical implementation. Based on our prototype, we analyze the feasibility and applicability of incorporating reflective capabilities into different parts of EEs. Furthermore, the evaluation demonstrates the opportunities such reflective capabilities provide for unanticipated dynamic adaptation scenarios, benefiting thus, a wider range of users

Fully Reflective Execution Environments: Virtual Machines for More Flexible Software

VMs are complex pieces of software that implement programming language semantics in an efficient, portable, and secure way. Unfortunately, mainstream VMs provide applications with few mechanisms to alter execution semantics or memory management at run time. We argue that this limits the evolvability and maintainability of running systems for both, the application domain, e.g., to support unforeseen requirements, and the VM domain, e.g., to modify the organization of objects in memory. This work explores the idea of incorporating reflective capabilities into the VM domain and analyzes its impact in the context of software adaptation tasks. We characterize the notion of a fully reflective VM, a kind of VM that provides means for its own observability and modifiability at run time. This enables programming languages to adapt the underlying VM to changing requirements. We propose a reference architecture for such VMs and present TruffleMATE as a prototype for this architecture. We evaluate the mechanisms TruffleMATE provides to deal with unanticipated dynamic adaptation scenarios for security, optimization, and profiling aspects. In contrast to existing alternatives, we observe that TruffleMATE is able to handle all scenarios, using less than 50 lines of code for each, and without interfering with the application's logic

Diabetes, Pancreatogenic Diabetes, and Pancreatic Cancer

The relationships between diabetes and pancreatic ductal adenocarcinoma (PDAC) are complex. Longstanding type 2 diabetes (T2DM) is a risk factor for pancreatic cancer, but increasing epidemiological data point to PDAC as also a cause of diabetes due to unknown mechanisms. New-onset diabetes is of particular interest to the oncology community as the differentiation of new-onset diabetes caused by PDAC as distinct from T2DM may allow for earlier diagnosis of PDAC. To address these relationships and raise awareness of the relationships between PDAC and diabetes, a symposium entitled Diabetes, Pancreatogenic Diabetes, and Pancreatic Cancer was held at the American Diabetes Association's 76th Scientific Sessions in June 2016. This article summarizes the data presented at that symposium, describing the current understanding of the interrelationships between diabetes, diabetes management, and pancreatic cancer, and identifies areas where additional research is needed

Blood Transfusion Management for Patients Treated With Anti-CD38 Monoclonal Antibodies

Daratumumab has proven to be highly efficacious for relapsed and refractory multiple myeloma (MM) and has recently been approved in the frontline setting for MM patients ineligible for transplantation. In the future, expanded indications are possible for daratumumab and other anti-CD38 monoclonal antibodies in development. For several years, it has been recognized that these therapies interfere with blood bank testing by binding to CD38 on red blood cells and causing panagglutination on the Indirect Antiglobulin Test. This can lead to redundant testing and significant delays in patient care. Given the anticipated increase in utilization of anti-CD38 monoclonal antibodies, as well as the transfusion needs of MM patients, it is critical to understand the nature of this interference with blood bank testing and to optimize clinical and laboratory procedures. In this review, we summarize the pathophysiology of this phenomenon, examine the clinical data reported to date, describe currently available methods to resolve this issue, and lastly provide a guide to clinical management of blood transfusions for patients receiving anti-CD38 monoclonal antibodies