OPTIMIZING THE JAVA VIRTUAL MACHINE INSTRUCTION SET BY ...

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150 sequence will be handled by a subsequent iteration of the outside loop since it processes the sequences from longest to shortest, and the suffix sequence is guaranteed to be shorter e. Consequently, an arbitrary number of multicodes can be determined by repeatedly using FindBestSeq from Figure 7.4 and the update algorithm from Figure 7.5, without the need to determine all subsequences of the blocks listed in the compressed multicode block file multiple times. 7.3.5 A Simple Alternative Scoring Technique All of the examples discussed to this point have assumed that the score for a multicode was computed as the number of occurrences of the bytecode sequence multiplied by the length of the sequence. Consequently, the score for the multicode is the total number of bytecodes that will be directly impacted by the substitution. Using the notation expressed in the previous section, the total bytecodes substituted would be expressed as: T otalBytecodesScore = N x1 /x 2 /x 3 /.../x n→ × n (7.14) A simple alternative to this scoring technique is counting the number of transfers removed by performing the substitution. Computing the score in this manner effectively assumes that the change in performance due to transfer reductions is much larger than the change in performance due to optimization potential within the sequence and other factors such as the impact on caching. Under this system, the score for any potential multicode becomes: T ransferReductionScore = N x1 /x 2 /x 3 /.../x n→ × (n − 1) × Cost(→) (7.15) However, because the cost of a transfer is a constant cost in every score calculation, it can be assigned the value 1, simplifying the equation without impacting the relative ordering of the bytecode sequences under consideration. When this simplification is performed, the score represents the total number of transfers that will be removed as a result of performing the multicode substitution, remembering that a transfer of control must still be present after the multicode in order to reach the next bytecode or multicode in the method. T ransferReductionScore = N x1 /x 2 /x 3 /.../x n→ × (n − 1) (7.16)
151 Both the Total Bytecodes Score and the Transfer Reduction Score fail to consider the optimization potential of the sequence or the impact its replacement has on cache performance. Another scoring technique which attempts to capture of complete impact of the multicode’s impact including transfers removed, optimization potential and caching is discussed in Section 7.8. 7.4 Multicode Substitution Once a multicode is identified, the Java class files must be modified to make use of it. This process is referred to as multicode substitution. It involves examining the code stream within each class file in order to locate occurrences of the bytecode sequence to replace with the multicode. However, performing multicode substitution is not as simple as replacing all occurrences of the bytecode sequence with the new multicode. Branching, exceptions, and the difference in size between the multicode and the sequence of bytecodes that it represents all must be taken into consideration. Checks were performed during profiling in order to ensure that only those sequences that can be replaced contribute to the score of each multicode. However, those checks do not guarantee the absence of other occurrences of the sequence that are ineligible for substitution within the class files. As a result, care must be taken during the substitution process. Branching presents difficulties because it is not possible to branch to the middle of a multicode – either the entire multicode executes or the entire multicode does not execute. Consequently, it is not possible to perform a multicode substitution on any sequence of bytecodes, x 1 →x 2 →x 3 →... →x n →, where a bytecode in the sequence, other than x 1 , is a target of a branch, conditional or unconditional. The lookupswitch and tableswitch bytecodes are treated as a special type of conditional branch that has multiple branch targets. If such a substitution was performed, there would be no way to express the target of the branch bytecode. Branching to the start of the multicode would result in bytecodes being executed that were not executed before the substitution was performed, potentially placing values with inconsistent types on the operand stack or otherwise resulting in incorrect results being generated. The same situation can occur if the branch target was set to the bytecode immediately following the multicode. Exception handlers are represented within the Java Virtual Machine by specifying the program counter value for the first bytecode within the exception handler and the first bytecode that is not covered by the exception handler. As a result, a similar
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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
Page 117 and 118: 99 Within this category, it was als
Page 119 and 120: 101 machine code for the idioms. As
Page 121 and 122: 103 were performed was less than 0.
Page 123 and 124: 105 these despecializations in a me
Page 125 and 126: 107 Chapter 6 Operand Profiling Cha
Page 127 and 128: 109 the applications. In addition,
Page 129 and 130: 111 The aload 0 bytecode was the mo
Page 131 and 132: 113 function being integrated. Beca
Page 133 and 134: 115 Implementing alignment rules un
Page 135 and 136: 117 these data types in the list of
Page 137 and 138: Figure 6.3: Distribution of Local V
Page 139 and 140: 121 are never executed by any of th
Page 141 and 142: 123 load and store bytecodes. It is
Page 143 and 144: 125 the time because the index bein
Page 145 and 146: 127 6.2.5 Fields Only four bytecode
Page 147 and 148: 129 Figure 6.8: Data types Accessed
Page 149 and 150: 131 lar, the new set of specialized
Page 151 and 152: 133 multicode block is defined to b
Page 153 and 154: 135 Figure 7.1: Two Bytecodes and t
Page 155 and 156: 137 because of the presence of the
Page 157 and 158: 139 cache performance. As a result,
Page 159 and 160: 141 Block 1: Block 2: aload 0 → g
Page 161 and 162: 143 Sequence Count Score getfield a
Page 163 and 164: Figure 7.3: Iterative Multicode Ide
Page 165 and 166: 147 number of bytecodes that will b
Page 167: 149 BlockList: A list of the byteco
Page 171 and 172: 153 ... i − 1 ❄ ifeq 0x00 0x15
Page 173 and 174: 155 Figure 7.7: Number of Unique Ca
Page 175 and 176: Figure 7.9: Cumulative Multicode Bl
Page 177 and 178: 159 However, while considering long
Page 179 and 180: 161 Figure 7.10: 201 compress Perfo
Page 181 and 182: 163 Figure 7.14: Length 209 db Perf
Page 183 and 184: 165 Figure 7.18: 222 mpegaudio Perf
Page 185 and 186: 167 7.6.2 Overall Performance Acros
Page 187 and 188: 169 a larger portion of the instruc
Page 189 and 190: 171 // iload_1: stack[sp+1] = local
Page 191 and 192: 173 // iload_1: // iconst_1: // iad
Page 193 and 194: 175 Such bytecodes have a variable
Page 195 and 196: 177 ∆ x1 /x 2 /x 3 /.../x n→ an
Page 197 and 198: 179 Popping any values left on the
Page 199 and 200: 181 7.9 Conclusion This chapter has
Page 201 and 202: 183 ated will differ from that occu
Page 203 and 204: 185 Figure 8.1: A Comparison of the
Page 205 and 206: 187 performed impacts the sequences
Page 207 and 208: 189 Figure 8.2: 201 compress Perfor
Page 209 and 210: 191 Figure 8.5: 213 javac Performan
Page 211 and 212: 193 Compared to the complete despec
Page 213 and 214: 195 Figure 8.10: 209 db Performance
Page 215 and 216: 197 performing multicode substituti
Page 217 and 218: 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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209 Algorithm CountUniqueOccurrence
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211 this algorithm did not consider
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213 exceptions if the value being c
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215 Figure 10.1: Multicode Blocks u
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217 approximately 30 percent of the
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219 a strategy other than direct th
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221 10.2.6 Combining Multicodes and
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223 10.2.9 Expanding the Class File
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225 revealed that none of the const
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227 based on these profile results
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229 stitution were performed. It co
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231 [13] B. Alpern, C. R. Attanasio
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233 [33] K. Casey, D. Gregg, M. A.
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235 [55] D. Gregg and J. Waldron. P
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237 [78] E. M. McCreight. A space-e
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239 [100] L. A. Smith, J. M. Bull,
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241 [120] T. A. Welch. A technique
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243 # Len Score Multicode % 1 30 10
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253 Table A.5 continued: # Len Scor
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259 the level of entropy within the
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261 there are no pointers to these
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263 information for each method so
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265 to emit four files that were su
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Figure B.1: The Steps Followed to E
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269 B.7 Summary This Chapter has de
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271 Selected Honors and Awards Cont
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273 Departmental and University Pre
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