OPTIMIZING THE JAVA VIRTUAL MACHINE INSTRUCTION SET BY ...

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$LATEX for Philosophers - University of Calgary$

84 Hardware Processors / Memory Operating System Virtual Machine(s) Clock Intel PIII 2 @ 600MHz 256MB Redhat Linux kernel Sun Java build 1.4.2 02-b03, mixed mode 2.4.20-20.9smp Jikes RVM 2.3.1 GNU Classpath 0.07, Production Intel P4 2 @ 2.8GHz 1GB Debian Linux kernel Sun Java build 1.4.2 04-b05, mixed mode 2.6.7-1-686-smp Jikes RVM 2.4.1 GNU Classpath 0.18, Production Intel 1 @ 1.7GHz 1GB Windows XP Home Sun Java build 1.5.0 05-b05, mixed mode Pentium M Service Pack 2 Sun Java build 1.5.0 05-b05, interpreted mode Sun Blade 100 1 @ 502MHz 128MB Sun OS 5.8 Solaris VM build Solaris JDK 1.2.2 10, UltraSPARC-IIe Generic 117350-29 native threads, sunwjit Sun Fire 280R 2 @ 900MHz 2GB Sun OS 5.8 Sun Java build 1.4.2 06-b03, mixed mode UltraSPARC-III+ Generic 108528-27 Table 5.2: Configurations Tested
Figure 5.1: Average Performance Results across All Test Configurations 85
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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
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 and 88: 69 4.2.6 Performance Summary Compar
Page 89 and 90: 71 Category Original Desp. Percent
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: 83 provided by only two vendors. IB
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
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
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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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