Witawas Srisa-an

Active memory processor: a hardware garbage collector for real-time Java embedded devices

Java possesses many advantages for embedded system development, including fast product deployment, portability, security, and a small memory footprint. As Java makes inroads into the market for embedded systems, much effort is being invested in designing real-time garbage collectors. The proposed garbage-collected memory module, a bitmap-based processor with standard DRAM cells is introduced to improve the performance and predictability of dynamic memory management functions that include allocation, reference counting, and garbage collection. As a result, memory allocation can be done in constant time and sweeping can be performed in parallel by multiple modules. Thus, constant time sweeping is also achieved regardless of heap size. This is a major departure from the software counterparts where sweeping time depends largely on the size of the heap. In addition, the proposed design also supports limited-field reference counting, which has the advantage of distributing the processing cost throughout the execution. However, this cost can be quite large and results in higher power consumption due to frequent memory accesses and the complexity of the main processor. By doing reference counting operation in a coprocessor, the processing is done outside of the main processor. Moreover, the hardware cost of the proposed design is very modest (about 8000 gates). Our study has shown that 3-bit reference counting can eliminate the need to invoke the garbage collector in all tested applications. Moreover, it also reduces the amount of memory usage by 77 percent.

SimRT: an automated framework to support regression testing for data races

Concurrent programs are prone to various classes of difficult-to-detect faults, of which data races are particularly prevalent. Prior work has attempted to increase the cost-effectiveness of approaches for testing for data races by employing race detection techniques, but to date, no work has considered cost-effective approaches for re-testing for races as programs evolve. In this paper we present SimRT, an automated regression testing framework for use in detecting races introduced by code modifications. SimRT employs a regression test selection technique, focused on sets of program elements related to race detection, to reduce the number of test cases that must be run on a changed program to detect races that occur due to code modifications, and it employs a test case prioritization technique to improve the rate at which such races are detected. Our empirical study of SimRT reveals that it is more efficient and effective for revealing races than other approaches, and that its constituent test selection and prioritization components each contribute to its performance.

Clustering the heap in multi-threaded applications for improved garbage collection

Garbage collection can be a performance bottleneck in large distributed, multi-threaded applications. Applications may produce millions of objects during their lifetimes and may invoke hundreds or thousands of threads. When using a single shared heap, each time a garbage collection phase occurs all threads must be stopped, essentially halting all other processing. Attempts to fix this bottleneck include creating a single heap per thread, however this may not scale to large thread intensive applications. In this paper we explore the potential of clustering threads into related sub-heaps. We hypothesize that this will lead to a smaller shared heap, while maintaining good garbage collection parallelism. We leverage results from software module clustering to achieve this goal. Our results show that we can significantly reduce the number of sub-heaps created and reduce the number of objects in the shared heap in a representative application. This suggests that clustering may be a promising optimization technique for garbage collection in large multi-threaded systems with many shared objects.

SimTester: a controllable and observable testing framework for embedded systems

In software for embedded systems, the frequent use of interrupts for timing, sensing, and I/O processing can cause concurrency faults to occur due to interactions between applications, device drivers, and interrupt handlers. This type of fault is considered by many practitioners to be among the most difficult to detect, isolate, and correct, in part because it can be sensitive to execution interleavings and often occurs without leaving any observable incorrect output. As such, commonly used testing techniques that inspect program outputs to detect failures are often ineffective at detecting them. To test for these concurrency faults, test engineers need to be able to control interleavings so that they are deterministic. Furthermore, they also need to be able to observe faults as they occur instead of relying on observable incorrect outputs. In this paper, we introduce SimTester, a framework that allows engineers to effectively test for subtle and non-deterministic concurrency faults by providing them with greater controllability and observability. We implemented our framework on a commercial virtual platform that is widely used to support hardware/software co-designs to promote ease of adoption. We then evaluated its effectiveness by using it to test for data races and deadlocks. The result shows that our framework can be effective and efficient at detecting these faults.

Microphase: an approach to proactively invoking garbage collection for improved performance

To date, the most commonly used criterion for invoking garbage collection (GC) is based on heap usage; that is, garbage collection is invoked when the heap or an area inside the heap is full. This approach can suffer from two performance shortcomings: untimely garbage collection invocations and large volumes of surviving objects. In this work, we explore a new GC triggering approach called MicroPhase that exploits two observations: (i) allocation requests occur in phases and (ii) phase boundaries coincide with times when most objects also die. Thus, proactively invoking garbage collection at these phase boundaries can yield high efficiency. We extended the HotSpot virtual machine from Sun Microsystems to support MicroPhase and conducted experiments using 20 benchmarks. The experimental results indicate that our technique can reduce the GC times in 19 applications. The differences in GC overhead range from an increase of 1% to a decrease of 26% when the heap is set to twice the maximum live-size. As a result, MicroPhase can improve the overall performance of 13 benchmarks. The performance differences range from a degradation of 2.5% to an improvement of 14%.

Performance enhancements to the Active Memory System

The Active Memory System - a garbage collected memory module - was introduced as a way to provide hardware support for garbage collection in embedded systems. The major component in the design was the Active Memory Processor (AMP) that utilized a set of bit-maps and a combinational circuit to perform mark-sweep garbage collection. The design can achieve constant time for both allocation and sweeping. In this paper two enhancements are made to the design of AMP so that it can perform one-bit reference counting that postpones the need to perform garbage collection. Moreover, a caching mechanism is also introduced to reduce the hardware cost of the design. The experimental results show that the proposed modification can reduce the number of garbage collection invocations by 76%. The speed-up in marking time can be as much as 5.81. With the caching mechanism, the hardware cost can be as small as 27 K gates and 6 KB of SRAM.

DMMX: dynamic memory management extensions

Dynamic memory management allows programmers to be more productive and increases system reliability and functionality. However, software algorithms for memory management are slow and non-deterministic. It is well known that object-oriented applications tend to be dynamic memory intensive. This has led programmers to eschew dynamic memory allocation for many real-time and embedded systems. Instead, programmers using Java or C++ as a development language frequently decide to allocate memory statically instead of dynamically. In this paper, we present the design of a bitmap-based memory allocator implemented primarily in combinational logic to allocate memory in a small, predictable amount of time. It works in conjunction with an application-specific instruction-set extension called the dynamic memory management extension (DMMX). Allocation is done through a complete binary tree of combinational logic, which allows constant-time object creation. The garbage collection algorithm is mark sweep, where the sweeping phase can be accomplished in constant time. This hardware scheme can greatly improve the speed and predictability of dynamic memory management. The proposed DMMX is an add-on approach, which allows easy integration into any CPU, hardware-implemented Java virtual machine, or processor in memory.

SOS: saving time in dynamic race detection with stationary analysis

Data races are subtle and difficult to detect errors that arise during concurrent program execution. Traditional testing techniques fail to find these errors, but recent research has shown that targeted dynamic analysis techniques can be developed to precisely detect races (i.e., no false race reports are generated) that occur during program execution. Unfortunately, precise race detection is still too expensive to be used in practice. State-of-the-art techniques still slow down program execution by a factor of eight or more. In this paper, we incorporate an optimization technique based on the observation that many thread-shared objects are written early in their lifetimes and then become read-only for the remainder of their lifetimes; these are known as stationary objects. The main contribution of our work is the insight that once a stationary object becomes thread-shared, races cannot occur. Therefore, our proposed approach does not monitor access to these objects. As such, our system only incurs an average overhead of 45% of that of an implementation of FastTrack, a low-overhead dynamic race detector. We then compared the effectiveness of our approach to de- tect races in deployed environments with that of Pacer, a sampling based race detector based on FastTrack. We found that our approach can detect over five times more races than Pacer when we budget 50% for runtime overhead.

Architectural support for dynamic memory management

Recent advances in software engineering, such as graphical user interfaces and object-oriented programming, have caused applications to become more memory intensive. These applications tend to allocate dynamic memory prolifically. Moreover, automatic dynamic memory reclamation (garbage collection, GC) has become a popular feature in modern programming languages. As a result, the time consumed by dynamic storage management can be up to one-third of the program execution time. This illustrates the need for a high-performance memory management scheme. This paper presents a top-level design and evaluation of the proposed instruction extensions to facilitate heap management.

An energy efficient garbage collector for java embedded devices

This paper presents a detailed design and implementation of a power-efficient garbage collector for Java embedded systems. The proposed scheme is a hybrid between the standard mark-sweep-compact collector available in Suns KVM and a limited-field reference counter. There are three benefits resulting from the proposed scheme. (a) the proposed scheme reclaims memory more efficiently and this results in less mark-sweep garbage collection invocations, (b) reduction in garbage collection invocations improves cache locality and reduces the number of main memory accesses, and (c) reduction in memory access ultimately results in lower energy consumption, since a memory access can consume a large amount of energy when compared with an instruction execution. The proposed scheme has been implemented into Suns KVM, and has been shown to reduce the number of mark-sweep garbage collection invocations by up to 100% in some cases, and the number of level-1 cache misses by as much as 87% when compared to the default garbage collector. We also find that in some applications, the proposed scheme can reduce the power consumption by as much as 27% when compared to the default Suns KVM.