53244522
An energy efficient garbage collector for java embedded devices
39527990
FPGA-based reconfigurable computing
1021056
A performance perspective on the Active Memory System
Abstract One major problem of using Java in real-time and embedded devices is the non-deterministic turnaround time of dynamic memory management systems (memory allocation and garbage collection). For the allocation, the non-determinism is often contributed by the time to perform searching, splitting, and coalescing. For the garbage collection, the turnaround time is usually determined by the size of the heap, the number of live objects, the number of object collected, and the amount of garbage collected. Even with the current state-of-the-art garbage collectors (generational and incremental schemes), they may or may not guarantee the worst-case latency. Moreover, such schemes often prolong overall garbage collection time. In this paper, the performance analysis of the proposed Active Memory Module (AMM) for embedded systems is presented. Unlike the software counterparts, the AMM can perform a memory allocation in a predictable and bounded fashion (14 cycles). Moreover, it can also yield a bounded sweeping time regardless of the number of live objects or heap size. By utilizing the proposed system, the overall speedup can be as high as 23% compared to the garbage collection system of the JDK 1.2.2 running in classic mode.
18001825
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.
12198410
Scalable hardware-algorithm for mark-sweep garbage collection
The memory-intensive nature of object-oriented languages such as C++ and Java has created the need for high-performance dynamic memory management. Object-oriented applications often generate higher memory intensity in the heap region. Thus, a high-performance memory manager is needed to cope with such applications. As today's VLSI technology advances, it becomes increasingly attractive to map software algorithms such as malloc(), free() and garbage collection into hardware. This paper presents a hardware design of a sweeping function (for mark-and-sweep garbage collection) that fully utilizes the advantages of combinational logic. In our scheme, the bit sweep can detect and sweep the garbage in a constant time. Bit-map marking in software can improve the cache performance and reduce number of page faults; however, it often requires several instructions to perform a single mark. In our scheme, only one hardware instruction is required per mark. Moreover, since the complexity of the sweeping phase is often higher than the marking phase, the garbage collection time may be substantially improved. The hardware complexity of the proposed scheme (bit-sweeper) is O(n), where n represents the size of the bit map.
9645285
Using scratchpad to exploit object locality in Java
Performance of modern computers is tied closely to the effective use of cache because of the continually increasing speed discrepancy between processors and main memory. We demonstrate that generational garbage collection employed by a system with cache and scratchpad memory can take advantage of the locality of small short-lived objects in Java and reduce memory traffic by as much as 20% when compared to a cache-only configuration. Converting half of the cache to scratchpad can be more effective at reducing memory traffic than doubling or even quadrupling the size of the cache for several of the applications in SPECjvm98.
17161223
Speculative incoherent cache protocols
Multiprocessing and multithreading are becoming ubiquitous even on single chips. With increasing cache sizes, coherence misses in such systems will account for a larger fraction of all cache misses. As communication latencies increase, this larger fraction of coherence misses will cause significant and increased performance losses. Tuning coherence protocols for specific communication patterns and applications can reduce communication latencies. However, these optimizations increase a protocol's design complexity, making the protocol difficult to verify. A competing approach requires parallel programmers to tune applications to work well with simpler protocols. Speculative execution has successfully improved performance in various scenarios. We propose a new type of load speculation, called coherence decoupling. Coherence decoupling is a microarchitectural mechanism that implements separate protocols for speculative use and for the eventual verification of values. The technique reduces the effect of long communication latencies while mitigating the burdens on the coherence protocol designer and the parallel programmer
35558441
Using Interface Refinement to Integrate Formal Verification into the Design Cycle
We present a practical compositional interface refinement methodology which helps to integrate formal verification with the design process. One of the main verification challenges is to keep up with the changes to the specifications as the design evolves, and in particular, the transformations to the interfaces between the components. Interface changes are usually incremental, and therefore, the verification efforts after each change should also be incremental in order to be scalable. This paper presents a compositional interface refinement methodology which addresses all of these issues.
34947079
On the powers of graphs with bounded asteroidal number
Abstract For an undirected graph G =( V , E ), the kth power G k is the graph with the same vertex set as G such that two vertices are adjacent in G k if and only if their distance in G is at most k. A set of vertices A ⊆ V is an asteroidal set if for every vertex a ∈ A , the set A ⧹{ a } is contained in one connected component of G − N G [ a ], where N G [ a ] is the closed neighborhood of a in G. The asteroidal number of a graph G is the maximum cardinality of an asteroidal set in G. The class of graphs with asteroidal number at most s is denoted by A (s) . In this paper, we show that if G k ∈ A (s) for s ⩾2, then so is G k +1 . This generalizes a previous result for the family of AT-free graphs. Moreover, we consider the forbidden configurations for the powers of graphs with bounded asteroidal number. Based on these forbidden configurations, we show that every proper power of AT-free graphs is perfect.
14591723
A Sliding Window Method for Finding Recently Frequent Itemsets over Online Data Streams
A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Consequently, the knowledge embedded in a data stream is likely to be changed as time goes by. However, most of miming algorithms or frequency approximation algorithms for a data stream do not able to extract the recent change of information in a data stream adaptively. This paper proposes a sliding window method of finding recently frequent itemsets over an online data stream. The size of a window defines a desired life-time of the information of a transaction in a data stream.
17498259
estWin: adaptively monitoring the recent change of frequent itemsets over online data streams
Knowledge embedded in a data stream is likely to be changed as time goes by. Consequently, identifying the recent change of the knowledge quickly can provide valuable information for the analysis of the data stream. However, most of mining algorithms or frequency approximation algorithms for a data stream do not able to extract the recent change of information in a data stream adaptively. This paper proposes a sliding window-based method that finds recently frequent itemsets over an online data stream adaptively. The size of a window defines a desired life-time of the information in a newly generated transaction. Consequently, only recently generated transactions in the range of the window are considered to find the frequent itemsets of a data stream.