OPTIMIZING THE JAVA VIRTUAL MACHINE INSTRUCTION SET BY ...

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24 ... i − 1 iload 0 iload 1 iadd iload 2 i i + 1 i + 2 i + 3 ... i + 4 Figure 2.7: A Code Stream Containing Integer Load and Addition Bytecodes Consider the bytecode sequence iload 0 iload 1 iadd iload 2 shown in Figure 2.7. The branches performed when this sequence is executed are shown in Figure 2.8. Branches in this diagram have been numbered from 1 through 4, representing the order in which they occur. Notice that a total of only four branches are required in order to execute this sequence of bytecodes. Using a loop and switch statement optimized with goto statements would have required 8 branches in order to accomplish the same task. Twelve branches would have been necessary in order to accomplish this task using the naive implementation that utilized a while loop, presented initially. 2.4.4 Direct Threading Moving from indirect threading to direct threading reduces the amount of work that must be performed at the end of each codelet in order to reach the implementation of the next bytecode in the code stream. However, this is accomplished at the cost of increasing the overall size of the code stream. Direct threading [19] is accomplished by replacing the bytecodes that make up the code stream with the addresses of their codelets. Such a substitution increases the size of the opcodes from one byte to four bytes on most platforms. The number of bytes used to store the operand bytes is normally increased to the next multiple of four as well. Consequently, transferring control to the codelet representing the next bytecode requires dereferencing only one array compared to the two dereferences performed when indirect threading is employed. This is illustrated in Figure 2.9 which shows the branches performed in order to execute the bytecode sequence iload 0 iload 1 iadd iload 2. Direct threading also presents additional optimization opportunities beyond the reduction in array dereferencing operations. It is well suited to opcode transformations which replace constant pool offsets with pointers directly to the method or field in question because the number of operand bytes is increased to the next multiple of four. It is also possible to use selective inlining in conjunction with direct threading in
25 Figure 2.8: Interpreter Engine Constructed Using Indirect Threading order to reduce the total number of transfers of control performed in order to execute the application. This technique is discussed in Section 3.1.3. 2.4.5 Just-In-Time (JIT) Compilation The first Java virtual machines developed executed bytecodes using an interpreter. In the simplest form, this involves a fetch-decode-execute loop which repeatedly fetches and executes bytecodes. Unfortunately a great deal of time is spent executing the machine language instructions that make up this loop and the fetch / decode operations instead of executing the bodies of the instructions that represent the users application. A just-in-time (JIT) compiler can be used to overcome this problem. A JIT compiler translates Java bytecodes to machine language instructions at
Page 1 and 2: OPTIMIZING THE JAVA VIRTUAL MACHINE
Page 3 and 4: Abstract Since its public introduct
Page 5 and 6: Acknowledgments While my name is th
Page 7 and 8: 2.4.4 Direct Threading . . . . . .
Page 9 and 10: 7.2 An Overview of Multicodes . . .
Page 11 and 12: List of Figures 2.1 Core Virtual Ma
Page 13 and 14: 7.11 201 compress Performance by Mu
Page 15 and 16: B.1 The Steps Followed to Evaluate
Page 17 and 18: 6.1 Most Frequently Occurring Const
Page 19 and 20: 1 Chapter 1 Introduction When Moore
Page 21 and 22: 3 Studies were conducted that consi
Page 23 and 24: 5 Chapter 2 An Overview of Java Thi
Page 25 and 26: 7 Addressing this need led to the d
Page 27 and 28: 9 performs garbage collection, a cl
Page 29 and 30: 11 also has the ability to contain
Page 31 and 32: 13 ... i − 1 iload 0x04 dstore 0x
Page 33 and 34: 15 ... aload 3 iconst 2 faload ...
Page 35 and 36: 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: 23 Figure 2.6: 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 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
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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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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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