OPTIMIZING THE JAVA VIRTUAL MACHINE INSTRUCTION SET BY ...

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$LATEX for Philosophers - University of Calgary$

30 The first line in Figure 2.10 shows the declaration of the function that contains the execution loop. Three parameters must be provided to this function. The first parameter, method, is a pointer to a structure (or class) which contains information about a method. This includes its name, the class it resides in, its signature, and the bytecodes that implement its functionality, among other important values. The second parameter, callingStack, is a pointer to the operand stack in the scope that just invoked a new method. It is necessary to have a pointer to the stack in the calling scope in order to access the Java method’s parameters. The final parameter to the function, callingTop, is an integer that indicates which index in callingStack represents the top of the operand stack at the time the method was invoked. Lines 3 and 4 allocate the data structures that represent the call frame for the method being invoked. The first data structure allocated is the operand stack. The maximum number of elements that will reside on the stack is determined during compilation. As a result, the interpreter only needs to read this value from the method structure. Similarly, it is not difficult to allocate the correct amount of memory for the method’s local variables because the number of local variables that will be used is also stored within the method structure. The method’s parameters are passed on lines 6 through 10. This is accomplished by copying them from the operand stack in the calling scope into the local variables for the method being invoked. When the method being invoked is a static method with no parameters, no values are copied. Line 12 acquires a pointer to the constant pool for the method. This pointer is needed because some bytecodes read values from the constant pool during their execution. A pointer to the method’s code stream is acquired on Line 13. Lines 14 and 15 initialize the program counter, denoted by pc, and the next instruction program counter, denoted by npc, to 0. Using two indices into the code array reduces the cost of advancing the program counter to the index of the next instruction. Lines 18 and 19 update the values of pc and npc. Once the update is performed, pc points at the instruction which is about the execute and npc points at the instruction that will execute after it, unless the flow of control within the method is changed by a branch bytecode. Line 20 performs the decode operation in the interpreter’s main execution loop using a switch statement. When the switch statement executes, the flow of control will branch to the case which implements the bytecode indicated by code[pc]. The codelets for two bytecodes are shown on lines 21 through 31. Both of the
31 codelets shown in this example are small, as are the codelets for many of the bytecodes defined by the Java Virtual Machine Specification. Each codelet terminates with a goto statement which transfers the flow of control back to the top of the interpreter’s execution loop. 2.7 Summary This chapter has presented background information related to the Java Programming Language and Java Virtual Machines. It began by describing the historical events which lead to the creation of Java. This was followed by a description of a Java Virtual Machine, including different techniques that can be employed to implement a Java interpreter, a discussion of the core data structures within a Java Virtual Machine and an overview of the Java bytecodes that represent a Java application. This was followed by a list of several Java Virtual Machine implementations. Additional details were provided about the implementations considered in the studies presented later in this thesis. The chapter concluded with a detailed look at the code for a simple Java interpreter.
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 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: 29 execute (JMethod * method, Slot
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
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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
Page 289 and 290:
271 Selected Honors and Awards Cont
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273 Departmental and University Pre
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