OPTIMIZING THE JAVA VIRTUAL MACHINE INSTRUCTION SET BY ...

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70 constant pool due to a previous despecialization of bipush and the value resides at an index less than 256. When these constraints are met, replacing bipush with ldc does not increase the size of the code stream because both bipush and ldc require exactly two bytes: one for the opcode and one for the operand. A similar situation can also occur for sipush. In this instance, it is actually possible that performing despecialization will decrease the size of the class file. A one byte decrease will occur when the value being loaded already exists in the constant pool at an index less than 256. This occurs because despecializing sipush to ldc reduces the number of operand bytes that are required in the code stream from 2 bytes to 1 byte. In other instances, despecializing sipush will have no impact on class file size. This occurs when the value resides in the constant pool at an index greater than 255. Consequently, sipush must be despecialized to ldc w which also requires two operand bytes. In rare cases, despecialization will not increase class file size when bytecodes other than bipush and sipush are despecialized. This can occur when the despecializations are only performed on bytecodes that occur ahead of a lookupswitch or tableswitch bytecode that includes one or more pad bytes. When the despecialization is performed, the number of pad bytes is reduced in order to ensure that the alignment rules for the lookupswitch or tableswitch are still maintained, resulting in no change in class file size. However, in other cases, performing despecialization can require the introduction of pad bytes that were not required previously, potentially increasing the size of the class file by 3 bytes beyond the number of additional bytes introduced at the location within the code stream that is being despecialized. The impact despecialization had on class file size was measured. Complete despecialization was performed on all of the classes in the libraries provided by each of the virtual machines. Complete despecialization was also performed on all of the class files in the SPEC JVM98 Benchmark Suite except one. The file install.class was omitted from consideration because it includes a large non-standard attribute that can be used to install the benchmark suite. Including this file would have resulted in smaller class file size increase values. A summary of the class file size increase values is presented in Table 4.10. It shows the change in class file size observed for the classes that make up the SPEC JVM98 Benchmarks and the class files that make up the class libraries associated with each of the virtual machines. The first three columns of data report the average class file size observed before and after despecialization was performed, and the percentage change this difference represents. The final three columns of data examine the impact
71 Category Original Desp. Percent Original Desp. Percent Average Average Increase Maximum Maximum Increase SPEC Classes 2582 2745 6.3 35697 38381 7.5 Kaffe Library 1825 1929 5.7 26172 27743 6.0 RVM Library 2644 2785 5.3 283144 311148 9.9 Sun Library 2700 2870 6.3 122426 124213 1.5 Table 4.10: Despecialization’s Impact on Class File Size despecialization had on the largest class file within each group. It shows that the largest files were not necessarily the ones that showed the greatest increase in size due to despecialization. 4.4 Class File Correctness The despecialization rules outlined previously do not impact the computational power of the Java Virtual Machine. Furthermore, the rules make no semantic changes to the Java class files, with each despecialized form providing identical semantics compared to its corresponding specialized bytecode. However, despecializations do generally increase class file size. Consequently, size constraints imposed by the Java Virtual Machine Specification may be violated during the despecialization process, making it difficult to apply some despecialization rules. One size constraint dictated by the Java Virtual Machine Specification is the maximum size of a method’s code attribute. This constraint requires that no method exceed 65535 bytes in size. Consequently, it is possible that performing despecialization may take a very large method and make it even larger, resulting in a method in excess of the maximum size permitted. With some effort, such a method could automatically be split into two or more methods, resulting in two or more methods that are all within the required size. In practice such a problem was never encountered anywhere in any of the virtual machine’s libraries or within the class files that make up the SPEC JVM98 Benchmark Suite. Before despecialization was performed the longest method was 21104 bytes. This grew to 29697 bytes after complete despecialization was performed, still less than half of the maximum size permitted. Some of the despecializations considered previously have the potential to increase the number of elements in the constant pool. These include despecializing the bipush, sipush and const bytecodes. The Java Virtual machine specification restricts the number of elements in the constant pool to 65535. Consequently, it is
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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
Page 37 and 38: 19 transfered to the start of a new
Page 39 and 40: 21 piled into machine language inst
Page 41 and 42: 23 Figure 2.6: Interpreter Engine C
Page 43 and 44: 25 Figure 2.8: Interpreter Engine C
Page 45 and 46: 27 The following section examines t
Page 47 and 48: 29 execute (JMethod * method, Slot
Page 49 and 50: 31 codelets shown in this example a
Page 51 and 52: 33 3.1 Instruction Set Design The a
Page 53 and 54: 35 is replaced with a new opcode if
Page 55 and 56: 37 method. However, the Java Virtua
Page 57 and 58: 39 3.2.5 Bytecode Optimization Tool
Page 59 and 60: 41 each bytecode executed as was ac
Page 61 and 62: 43 executing the application. The a
Page 63 and 64: 45 Chapter 4 Despecialization The J
Page 65 and 66: 47 ... i − 1 iload 3 iload 0x04 i
Page 67 and 68: 49 purpose bytecodes. The notation,
Page 69 and 70: 51 is present in the constant pool
Page 71 and 72: 53 ... iload 3 iflt ... i − 1 i i
Page 73 and 74: 55 the stack challenging in some ca
Page 75 and 76: Figure 4.7: Despecialization of Bra
Page 77 and 78: 59 Specialized Bytecode load store
Page 79 and 80: 61 tual machine (RVM). Version 2.3.
Page 81 and 82: 63 Test Total Weighted Condition Pe
Page 87: 69 4.2.6 Performance Summary Compar
Page 91 and 92: 73 the maximum value encountered af
Page 93 and 94: 75 • Efficient support of new lan
Page 95 and 96: 77 difference in the performance of
Page 97 and 98: 79 JGF RayTracer: A 150 by 150 pixe
Page 99 and 100: 81 # Average % of Specialized Despe
Page 101 and 102: 83 provided by only two vendors. IB
Page 103 and 104: Figure 5.1: Average Performance Res
Page 105 and 106: 87 Figure 5.4: Performance Results
Page 107 and 108: 89 Figure 5.8: Performance Results
Page 109 and 110: 91 ences in background processes, m
Page 111 and 112: 93 difference in performance due to
Page 113 and 114: 95 when a pure interpreter virtual
Page 115 and 116: 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
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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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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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