• IEIE Transactions on Smart Processing and Computing
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• v.4 no.3
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• pp.169-172
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• 2015

Dalvik is a virtual machine (VM) that is designed to run Java-based Android applications. A trace-based just-in-time (JIT) compilation technique is currently employed to improve performance of the Dalvik VM. However, due to runtime compilation overhead, the trace-based JIT compiler provides only a few simple optimizations. Moreover, because each trace contains only a few instructions, the trace-based JIT compiler inherently exploits fewer optimization and parallelization opportunities than a method-based JIT compiler that compiles method-by-method. So we propose a new method-based JIT compiler, named DEX2C, in order to improve performance by finding more opportunities for both optimization and parallelization in Android applications. We employ C code as an intermediate product in order to find more optimization opportunities by using the GNU C Compiler (GCC), and we will detect parallelism by using the Intel C/C++ parallel compiler and the AESOP compiler in our future work. In this paper, we introduce our DEX2C compiler, which dynamically translates Dalvik bytecodes (DEX) into C code with method granularity. We also describe a new method-based JIT interface in the Dalvik VM for the DEX2C compiler. Our experiment results show that our compiler and its interface achieve significant performance improvement by up to 15.2 times and 3.7 times on average, in Element Benchmark, and up to 2.8 times for FFT in Smartbench.

• Geophysics and Geophysical Exploration
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• v.24 no.2
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• pp.35-44
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• 2021

As the execution speed of Python is slower than those of other programming languages (e.g., C, C++, and FORTRAN), Python is not considered to be efficient for writing numerical geodynamic code that requires numerous iterations. Recently, many computational techniques, such as the Just-In-Time (JIT) compiler, have been developed to enhance the calculation speed of Python. Here, we developed two-dimensional (2D) numerical geodynamic code that was optimized for the JIT compiler, based on Python. Our code simulates mantle convection by combining the Particle-In-Cell (PIC) scheme and the finite element method (FEM), which are both commonly used in geodynamic modeling. We benchmarked well-known mantle convection problems to evaluate the reliability of our code, which confirmed that the root mean square velocity and Nusselt number obtained from our numerical modeling were consistent with those of the mantle convection problems. The matrix assembly and PIC processes in our code, when run with the JIT compiler, successfully achieved a speed-up 30× and 258× faster than without the JIT compiler, respectively. Our Python-based FEM-PIC code shows the high potential of Python for geodynamic modeling cases that require complex computations.

• The KIPS Transactions:PartA
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• v.12A no.1 s.91
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• pp.59-64
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• 2005

In this paper, we propose a method of generating a JIT compiler using JBURG. JBURG is a tool of generating the code generator using bottom-up tree pattern matching for Java. Our method can be derived from some relations over tree patterns. The proposed scheme is more efficient than JBURG because we can avoid unfruitful tests with the smaller site of the scheme. Furthermore, the relevant analyses needed for this proposal are largely achieved at non- compile time, which secures actual efficiency at compilation time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11B
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• pp.1323-1328
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• 2011

In this paper, we have shown Dalvik virtual machine implementation to reduce the profiling overhead from the trace of the JIT compiler for the specific method. By running the same Java method on the original Dalvik VM and the modified Dalvik VM, we have achieved around 30% performance improvement with this algorithm. In this paper, to increase the reader's understanding of Android Dalvik virtual machine, we will explain the architecture of Dalvik JIT compiler and we will provide the detailed explanation with source codes for modified parts of Dalvik virtual machine. From the industry perspective, we can expect competitive benefits over the competitors with performance improvement in Android core.

• The Journal of Information Technology
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• v.4 no.1
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• pp.1-7
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• 2001

The well-known tradeoff of Java's portability is the inefficiency of its basic execution model, which relies on the interpretation of an virtual machine. Many solutions have been proposed to overcome this problem, such as just-in-time(JIT) and offline bytecode compilers. However, JIT compiler can not avoid the overhead of runtime. since it translate bytecode into native code at runtime. And, pure offline bytecode compiler limits the ability of dynamic class loading. In this paper, we present an approach which preserves the ability to dynamically load bytecode, and is more efficient than JIT. In contrast to existing bytecode-to-C translator using the old NMI, our translator maintain complete compatibility and portability through using the Java Native Interface(JNI) standard. We have designed and implemented an translator for converting bytecode to C code with JNI.. named MyJNItool.

• Journal of KIISE:Software and Applications
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• v.32 no.3
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• pp.215-226
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• 2005

Loop invariant code motion (LICM) optimization includes relatively heavy code analyses, thus being not readily applicable to Java Just-In-Time (JIT) compilation where the JIT compilation time is part of the whole running time. 'Classical' LICM optimization first analyzes the code and constructs both the def-use chains and the use-def chains. which are then used for performing code motions. This paper proposes a light-weight LICM algorithm, which requires only the def-use chains of loop invariant code (without use-def chains) by exploiting the fact that the Java virtual machine is based on a stack machine, hence generating code with simpler patterns. We also propose two techniques that allow more code motions than classical LICM techniques. First, unlike previous JIT techniques that uses LICM only in single-path loops for simplicity, we apply LICM to multi-path loops (natural loops) safely for partially redundant code. Secondly, we move loop-invariant, partially-redundant null pointer check code via predication support in Itanium. The proposed techniques were implemented in a JIT compiler for Itanium processor on ORP (Open Runtime Platform) Java virtual machine of Intel. On SPECjvrn98 benchmarks, the proposed technique increases the JIT compilation overhead by the geometric mean of 1.3％, yet it improves the total running time by the geometric mean of 2.2％.

• Journal of KIISE:Software and Applications
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• v.32 no.7
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• pp.683-692
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• 2005

Java specification states that all accesses to an object must be checked at runtime if object refers to null. Since Java is an object-oriented language, object accesses are frequent enough to make null pointer checks affect the performance significantly. In order to reduce the performance degradation, there have been attempts to remove redundant null pointer checks. For example, in a Java environment where a just-in-time (JIT) compiler is used, the JIT compiler removes redundant null pointer check code via code analysis. This paper proposes a technique to remove additional null pointer check code that could not be removed by previous JIT compilation techniques, via early null pointer check using an architectural feature called predication. Generally, null point check code consists of two instructions: a compare and a branch. Our idea is moving the compare instruction that is usually located just before an use of an object, to the point right after the object is defined so that the total number of compare instructions is reduced. This results in reduction of dynamic and static compare instructions by 3.21$\%$ and 1.98$\%$. respectively, in SPECjvm98 bechmarks, compared to the code that has already been optimized by previous null pointer check elimination techniques. Its performance impact on an Itanium machine is an improvement of 0.32$\%$.

• Journal of KIISE:Software and Applications
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• v.32 no.12
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• pp.1283-1291
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• 2005

One of the problems in boosting Java performance using a Just-in-Time (JIT) compiler is removing redundant array bound checks. In conventional static compilers, many powerful algorithms have been developed, yet they are not directly applicable to JIT compilation where the compilation time is part of the whole running time. In the current JIT compilers, we tan use either a naive algorithm that is not powerful enough or an aggressive algorithm which requires the transformation into a static single assignment (SSA) form of programs (and back to the original form after optimization), thus causing too much overhead not appropriate for JIT compilation This paper proposes a new algorithm based on an inequality graph which can eliminate array bounds check codes aggressively without resorting to the SSA form. When we actually perform this type of optimization, there are many constraints in code motion caused by the precise exception rule in Java specification, which would cause the algorithm to miss many opportunities for eliminating away bound checks. We also propose a new method to overcome these constraints.

• Journal of Information Technology Services
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• v.6 no.2
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• pp.145-152
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• 2007

This paper describes an extension of Kaffe JVM which enables to extract runtime characteristics of a Java program. The runtime characteristics include frequency of method call instruction, ratio of library method call and ratio of method whose runtime is less than compile time. It also represents ratio of method called only once, polymorphicity of virtual call and distribution of method size called in runtime. This paper analyses runtime features of the SciMark benchmark suite using the extended Kaffe.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.326-328
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• 2000

본 논문에서는 지연계산기반 함수형 언어 프로그램을 받아 Java 프로그램을 목적 코드로 생성하는 컴파일러를 설계하고 구현한다. 이 컴파일러는 제한된 형태의 함수형 언어 Shared Term Graph(STG)를 입력언어로 하는 추상기계 Spineless Tagiess G-Machine (STGM)을 수행 모델로 한다. 본 논문에서는 명령형 언어 L-code를 제안하고 이를 입력언어로 하는 새로운 형태의 STGM인 L-Machine을 제안한다. STG 언어를 L-code로 변환하는 컴파일러와 L-code를 Java로 변환하는 컴파일러를 설계하고 구현함으로써 원하는 컴파일러를 구성한다. 그리고 Glasgow Haskell 컴파일러를 전단부로 하여 지연계산 기반 함수형 언어 Haskell로 작성된 프로그램들을 컴파일하여 STG 프로그램으로 변환한 다음 본 논문에서 구현한 컴파일러로 이를 Java 프로그램으로 변환한다. 변환된 Java 프로그램을 Sun JIT 컴파일러로 컴파일하여 수행한 성능 평가 결과를 제시한다.