The disadvantages of unconstrained shared-memory multi-threading in Java, especially with regard to latency and determinism in realtime systems, have given rise to a variety of language extensions that place restrictions on how threads allocate, share, and communicate memory, leading to order-of-magnitude reductions in latency and jitter. However, each model makes different trade-offs with respect to expressiveness, efficiency, enforcement, and latency, and no one model is best for all applications. In this paper we present Flexible Task Graphs (Flexotasks), a single system that allows different isolation policies and mechanisms to be combined in an orthogonal manner, subsuming four previously proposed models as well as making it possible to use new combinations best suited to the needs of particular applications. We evaluate our implementation on top of the IBM Web-Sphere Real Time Java virtual machine using both a microbenchmark and a 30 KLOC avionics collision detector. We show that Flexotasks are capable of executing periodic threads at 10 KHz with a standard deviation of 1.2µs and that it achieves significantly better performance than RTSJ’s scoped memory constructs while remaining impervious to interference from global garbage collection.

Real-time Garbage Collection (RTGC) has recently advanced to the point where it is being used in production for financial trading, military command-and-control, and telecommunications. However, among potential users of RTGC, there is enormous diversity in both application requirements and deployment environments. Previously described RTGCs tend to work well in a narrow band of possible environments, leading to fragile systems and limiting adoption of real-time garbage collection technology. This paper introduces a collector scheduling methodology called tax-and-spend and the collector design revisions needed to support it. Tax-and-spend provides a general mechanism which works well across a variety of application, machine, and operating system configurations. Tax-and-spend subsumes the predominant pre-existing RTGC scheduling techniques. It allows different policies to be applied in different contexts depending on the needs of the application. Virtual machines can co-exist compositionally on a single machine. We describe the implementation of our system, Metronome-TS, as an extension of the Metronome collector in IBM’s Real-time J9 virtual machine product, and we evaluate it running on an 8-way SMP blade with a real-time Linux kernel. Compared to the stateof-the-art Metronome system on which it is based, implemented in the identical infrastructure, it achieves almost 3x shorter latencies, comparable utilization at a 2.5x shorter time window, and mean throughput improvements of 10-20%.

The Real-time Specification for Java extends the Java platform

Real-time Java is quickly emerging as a platform for building safety-critical embedded systems. The real-time variants of Java, including [8, 15], are attractive alternatives to Ada and C since they provide a cleaner, simpler, and safer programming model. Unfortunately, current real-time Java implementations have trouble scaling down to very hard real-time embedded settings, where memory is scarce and processing power is limited. In this paper, we describe the architecture of the Fiji VM, which enables vanilla Java applications to run in very hard environments, including booting on bare hardware with only very rudimentary operating system support. We also show that our minimalistic approach delivers comparable performance to that of server-class production Java Virtual Machine implementations. 1.

Automatic memory management or garbage collection greatly simplifies development of large systems. However, garbage collection is usually not used in real-time systems due to the unpredictable temporal behavior of current implementations of a garbage collector. In this paper we propose a real-time garbage collector that can be scheduled like a normal real-time thread with a deadline monotonic assigned priority. We provide an upper bound for the collector period so that the application threads will never run out of memory. Furthermore, we show that the restricted execution model of the Safety Critical Java standard simplifies root scanning and reduces copying of static data. Our proposal has been implemented and evaluated in the context of the Java processor JOP.

A real-time garbage collector has to fulfill two basic properties: ensure that programs with bounded allocation rates do not run out of memory and provide short blocking times. Even for incremental garbage collectors, two major sources of blocking exist, namely root scanning and heap compaction. Finding root nodes of an object graph is an integral part of tracing garbage collectors and cannot be circumvented. Heap compaction is necessary to avoid probably unbounded heap fragmentation, which in turn would lead to unacceptably high memory consumption. In this paper, we propose solutions to both issues. Thread stacks are local to a thread, and root scanning therefore only needs to be atomic with respect to the thread whose stack is scanned. This fact can be utilized by either blocking only the thread whose stack is scanned, or by delegating the responsibility for root scanning to the application threads. The latter solution eliminates blocking due to root scanning completely. The impact of this solution on the execution time of a garbage collector is shown for two different variants of such a root scanning algorithm. During heap compaction, objects are copied. Copying is usually performed atomically to avoid interference with application threads, which could render the state of an object inconsistent. Copying of large objects and especially large arrays introduces long blocking times that are unacceptable for real-time systems. In this paper an interruptible copy unit is presented that implements non-blocking object copy. The unit can be interrupted after a single word move. We evaluate a real-time garbage collector that uses the proposed techniques on a Java processor. With this garbage collector, it is possible to run high priority hard real-time tasks at 10 kHz parallel to the garbage collection task on a 100 MHz system. Categories and Subject Descriptors: C.3 [Special-Purpose and Application-Based Systems]: Real-time and embedded systems; D.3.4 [Programming Languages]: Processors—Memory management (garbage collection)

Achieving submillisecond response times in a managed language environment such as Java or C# requires overcoming significant challenges. In this article, we propose Reflexes, a programming model and runtime system infrastructure that lets developers seamlessly mix highly responsive tasks and timing-oblivious Java applications. Thus enabling gradual addition of real-time features, to a non-real-time application without having to resort to recoding the real-time parts in a different language such as C or Ada. Experiments with the Reflex prototype implementation show that it is possible to run a real-time task with a period of 45 μs with an accuracy of 99.996 % (only 0.001% worse than the corresponding C implementation) in the presence of garbage collection and heavy load ordinary Java threads.

While managed languages such as C # and Java have become quite popular in enterprise computing, they are still considered unsuitable for hard real-time systems. In particular, the presence of garbage collection has been a sore point for their acceptance for low-level system programming tasks. Realtime extensions to these languages have the dubious distinction of, at the same time, eschewing the benefits of highlevel programming and failing to offer competitive performance. The goal of our research is to explore the limitations of high-level managed languages for real-time systems programming. To this end we target a real-world embedded platform, the LEON3 architecture running the RTEMS real-time operating system, and demonstrate the feasibility of writing garbage collected code in critical parts of embedded systems. We show that Java with a concurrent, real-time garbage collector, can have throughput close to that of C programs and comes within 10 % in the worst observed case on realistic benchmark. We provide a detailed breakdown of the costs of Java features and their execution times and compare to real-time and throughput-optimized commercial Java virtual machines.

Achieving sub-millisecond response times in a managed language environment such as Java or C # requires overcoming significant challenges. In this paper we propose Reflexes, a programming model and runtime system infrastructure that lets developers seamlessly mix highly responsive tasks and timing-oblivious Java applications. Thus enabling gradual addition of real-time features, to a non-real-time application without having to resort to recoding the real-time parts in a different language such as C or Ada. Experiments with the Reflex prototype implementation show that it is possible to run a real-time task with a period of 45 µs with an accuracy of 99.996 % (only 0.001 % worse than the corresponding C implementation) in the presence of garbage collection and heavy load ordinary Java threads.

Large real-time software systems such as real-time Java virtual machines often use barrier protocols, which work for a dynamically varying number of threads without using centralized locking. Such barrier protocols, however, still suffer from priority inversion similar to centralized locking. We introduce gang priority management as a generic solution for avoiding unbounded priority inversion in barrier protocols. Our approach is either kernel-assisted (for efficiency) or library-based (for portability) but involves cooperation from the protocol designer (for generality). We implemented gang priority management in the Linux kernel and rewrote the garbage collection safe-point barrier protocol in IBM’s WebSphere Real Time Java Virtual Machine to exploit it. We run experiments on an 8-way SMP machine in a multi-user and multi-process environment, and show that by avoiding unbounded priority inversion, the maximum latency to reach a barrier point is reduced by a factor of 5.3 and the application jitter is reduced by a factor of 1.5. 1.