OPTIMIZING THE JAVA VIRTUAL MACHINE INSTRUCTION SET BY ...

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260 ceptions continue to identify the correct locations within the code stream once a rule has been applied to it. Retaining the correct branch and exception semantics is accomplished within the class file mutator by representing the bytecode stream as an ordered list of instruction objects rather than a sequence of bytes. When the code stream is translated into a list, all branch targets are expressed as pointers to other objects in the list rather than as offsets within the code stream. The multicode substitution is performed on the list representation. Once the substitution is complete, the bytecode stream is generated from the list representation by performing two passes. The first pass determines the program counter value for each of the instructions, including any pad bytes that need to be introduced within tableswitch and lookupswitch bytecodes. The bytecode stream is generated during the second pass. At that time, the branch targets expressed as pointers are replaced with the difference between the program counter of the current instruction and the instruction that is the target of the branch. Entries in the exception table are handled in a similar manner. Items in the exception table are converted from program counter values to pointers into the list of bytecodes immediately after the list representation is generated. The program counter representation of the exception table is regenerated immediately after the list of bytecodes is converted back into a byte stream. Consequently, appropriate changes will be made to the program counter values specified in the exception table for any changes made to the bytecode list. Care is taken to ensure that the pointers to entries in the list of bytecodes remain valid as the list is manipulated. When despecializations are performed the internal operations do not deallocate the bytecode object representing the specialized bytecode and then allocate a new bytecode object to represent its general purpose form. Instead, the opcode and operand values of the bytecode object are modified so that the object represents the equivalent general purpose form. If the general purpose form is a sequence of bytecodes then new bytecode objects are allocated to represent the bytecodes in the sequence beyond the first. Performing the manipulation in this manner removes the need to update any pointers in other data structures because the object that was the specialized bytecode before the transformation is the first (and possibly only) bytecode in the despecialized form after the despecialization. A similar strategy is employed for multicode substitution. In this case, the objects representing the second bytecode in the sequence and beyond are deallocated. It was determined that none of these bytecodes are targets of any branches or exception handlers before the substitution process began. Consequently, it is guaranteed that
261 there are no pointers to these bytecode objects in other data structures. Therefore, deallocating the objects will not cause any potential problems with the consistency of those data structures. The first bytecode in the sequence is not deallocated. Its opcode is changed to the target opcode specified in the substitution rule. Its operands are determined from the sequence of bytecodes that it replaces. Because the bytecode object was never deallocated, any pointers in any other data structures that pointed to the first bytecode in the sequence now point to the multicode, allowing the correct byte stream to be recreated at the end of the transformation process. In total, the bsub application consisted of 10 classes. The implementation of those classes and the application that made use of them required almost 10,000 lines of code. B.2 Data Collection Software Two different versions of the Kaffe virtual machine were created in order to gather the profile data used during the studies presented in this thesis. One version of the virtual machine was used to collect the data used in the despecialization studies presented in Chapter 5 and Chapter 6. This version recorded single bytecodes, including both the opcode and any operands present. The second modified version of the Kaffe virtual machine recorded the multicode blocks executed by the application. This version of the virtual machine only recorded opcodes, discarding all operand values. B.2.1 Operand Profiling Virtual Machine This version of the Kaffe virtual machine was modified to record each bytecode executed. The bytecodes were considered as discrete items. No information was recorded regarding the context in which the bytecode was executed. Modifications were made to the interpreter’s main execution engine. They consisted of inserting new function calls to record the desired information. The implementations of those functions were provided in a separate C++ source file. The information recorded by the modified virtual machine included both the opcode and its associated operands. Additional information from the constant pool was also recorded for some bytecodes. Recording this information was important because values can reside at different locations within the constant pool in different class files. Consequently, the operands specifying an offset into the constant pool are not sufficient in order to determine if similar values are being used in many files.
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OPTIMIZING THE JAVA VIRTUAL MACHINE
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Abstract Since its public introduct
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Acknowledgments While my name is th
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2.4.4 Direct Threading . . . . . .
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7.2 An Overview of Multicodes . . .
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List of Figures 2.1 Core Virtual Ma
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7.11 201 compress Performance by Mu
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B.1 The Steps Followed to Evaluate
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6.1 Most Frequently Occurring Const
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1 Chapter 1 Introduction When Moore
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3 Studies were conducted that consi
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5 Chapter 2 An Overview of Java Thi
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7 Addressing this need led to the d
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9 performs garbage collection, a cl
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11 also has the ability to contain
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13 ... i − 1 iload 0x04 dstore 0x
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15 ... aload 3 iconst 2 faload ...
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17 Condition Equal Unequal Greater
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19 transfered to the start of a new
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21 piled into machine language inst
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23 Figure 2.6: Interpreter Engine C
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25 Figure 2.8: Interpreter Engine C
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27 The following section examines t
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29 execute (JMethod * method, Slot
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31 codelets shown in this example a
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33 3.1 Instruction Set Design The a
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35 is replaced with a new opcode if
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37 method. However, the Java Virtua
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39 3.2.5 Bytecode Optimization Tool
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41 each bytecode executed as was ac
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43 executing the application. The a
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45 Chapter 4 Despecialization The J
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47 ... i − 1 iload 3 iload 0x04 i
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49 purpose bytecodes. The notation,
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51 is present in the constant pool
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53 ... iload 3 iflt ... i − 1 i i
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55 the stack challenging in some ca
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Figure 4.7: Despecialization of Bra
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59 Specialized Bytecode load store
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61 tual machine (RVM). Version 2.3.
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63 Test Total Weighted Condition Pe
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69 4.2.6 Performance Summary Compar
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71 Category Original Desp. Percent
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73 the maximum value encountered af
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75 • Efficient support of new lan
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77 difference in the performance of
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79 JGF RayTracer: A 150 by 150 pixe
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81 # Average % of Specialized Despe
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83 provided by only two vendors. IB
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Figure 5.1: Average Performance Res
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87 Figure 5.4: Performance Results
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89 Figure 5.8: Performance Results
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91 ences in background processes, m
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93 difference in performance due to
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95 when a pure interpreter virtual
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97 It is observed that many of the
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99 Within this category, it was als
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101 machine code for the idioms. As
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103 were performed was less than 0.
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105 these despecializations in a me
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107 Chapter 6 Operand Profiling Cha
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109 the applications. In addition,
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111 The aload 0 bytecode was the mo
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113 function being integrated. Beca
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115 Implementing alignment rules un
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117 these data types in the list of
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Figure 6.3: Distribution of Local V
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121 are never executed by any of th
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123 load and store bytecodes. It is
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125 the time because the index bein
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127 6.2.5 Fields Only four bytecode
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129 Figure 6.8: Data types Accessed
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131 lar, the new set of specialized
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133 multicode block is defined to b
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135 Figure 7.1: Two Bytecodes and t
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137 because of the presence of the
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139 cache performance. As a result,
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141 Block 1: Block 2: aload 0 → g
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143 Sequence Count Score getfield a
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Figure 7.3: Iterative Multicode Ide
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147 number of bytecodes that will b
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149 BlockList: A list of the byteco
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151 Both the Total Bytecodes Score
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153 ... i − 1 ❄ ifeq 0x00 0x15
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155 Figure 7.7: Number of Unique Ca
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Figure 7.9: Cumulative Multicode Bl
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159 However, while considering long
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161 Figure 7.10: 201 compress Perfo
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163 Figure 7.14: Length 209 db Perf
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165 Figure 7.18: 222 mpegaudio Perf
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167 7.6.2 Overall Performance Acros
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169 a larger portion of the instruc
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171 // iload_1: stack[sp+1] = local
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173 // iload_1: // iconst_1: // iad
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175 Such bytecodes have a variable
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177 ∆ x1 /x 2 /x 3 /.../x n→ an
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179 Popping any values left on the
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181 7.9 Conclusion This chapter has
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183 ated will differ from that occu
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185 Figure 8.1: A Comparison of the
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187 performed impacts the sequences
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189 Figure 8.2: 201 compress Perfor
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191 Figure 8.5: 213 javac Performan
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193 Compared to the complete despec
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195 Figure 8.10: 209 db Performance
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197 performing multicode substituti
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199 Chapter 9 An Efficient Multicod
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201 alphabet employed by each of th
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9.4 An Algorithm for the Most Contr
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Figure 9.3: The Impact of Algorithm
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207 Algorithm NonOverlappingScore(n
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Page 229 and 230: 211 this algorithm did not consider
Page 231 and 232: 213 exceptions if the value being c
Page 233 and 234: 215 Figure 10.1: Multicode Blocks u
Page 235 and 236: 217 approximately 30 percent of the
Page 237 and 238: 219 a strategy other than direct th
Page 239 and 240: 221 10.2.6 Combining Multicodes and
Page 241 and 242: 223 10.2.9 Expanding the Class File
Page 243 and 244: 225 revealed that none of the const
Page 245 and 246: 227 based on these profile results
Page 247 and 248: 229 stitution were performed. It co
Page 249 and 250: 231 [13] B. Alpern, C. R. Attanasio
Page 251 and 252: 233 [33] K. Casey, D. Gregg, M. A.
Page 253 and 254: 235 [55] D. Gregg and J. Waldron. P
Page 255 and 256: 237 [78] E. M. McCreight. A space-e
Page 257 and 258: 239 [100] L. A. Smith, J. M. Bull,
Page 259 and 260: 241 [120] T. A. Welch. A technique
Page 261 and 262: 243 # Len Score Multicode % 1 30 10
Page 271 and 272: 253 Table A.5 continued: # Len Scor
Page 277: 259 the level of entropy within the
Page 281 and 282: 263 information for each method so
Page 283 and 284: 265 to emit four files that were su
Page 285 and 286: Figure B.1: The Steps Followed to E
Page 287 and 288: 269 B.7 Summary This Chapter has de
Page 289 and 290: 271 Selected Honors and Awards Cont
Page 291: 273 Departmental and University Pre
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