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David Gregg
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- affiliation: Trinity College Dublin, Ireland
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2020 – today
- 2024
- [j40]Khalid Javeed, Ali El-Moursy, David Gregg:
E2CSM: efficient FPGA implementation of elliptic curve scalar multiplication over generic prime field GF(p). J. Supercomput. 80(1): 50-74 (2024) - [i31]Gul Aftab Ahmed, James Vincent Patten, Yuanhua Han, Guoxian Lu, David Gregg, Jim Buckley, Muslim Chochlov:
Using Ensemble Inference to Improve Recall of Clone Detection. CoRR abs/2402.07523 (2024) - 2023
- [j39]Khalid Javeed
, Ali El-Moursy
EC-Crypto: Highly Efficient Area-Delay Optimized Elliptic Curve Cryptography Processor. IEEE Access 11: 56649-56662 (2023) - [j38]Syed Asad Alam
On the RTL Implementation of FINN Matrix Vector Unit. ACM Trans. Embed. Comput. Syst. 22(6): 94:1-94:27 (2023) - [c66]Gul Aftab Ahmed, James Vincent Patten, Yuanhua Han, Guoxian Lu, David Gregg, Jim Buckley, Muslim Chochlov:
Using Ensemble Inference to Improve Recall of Clone Detection. IWSC 2023: 15-21 - [c65]Midia Reshadi, David Gregg:
Dynamic Resource Partitioning for Multi-Tenant Systolic Array Based DNN Accelerator. PDP 2023: 76-83 - [i30]Midia Reshadi, David Gregg:
Dynamic Resource Partitioning for Multi-Tenant Systolic Array Based DNN Accelerator. CoRR abs/2302.10806 (2023) - [i29]Midia Reshadi, David Gregg:
Maple: A Processing Element for Row-Wise Product Based Sparse Tensor Accelerators. CoRR abs/2303.15199 (2023) - [i28]Muslim Chochlov, Gul Aftab Ahmed, James Vincent Patten, Guoxian Lu, Wei Hou, David Gregg, Jim Buckley:
Using a Nearest-Neighbour, BERT-Based Approach for Scalable Clone Detection. CoRR abs/2309.02182 (2023) - 2022
- [j37]Khalid Javeed
High-speed parallel reconfigurable Fp multipliers for elliptic curve cryptography applications. Int. J. Circuit Theory Appl. 50(4): 1160-1173 (2022) - [j36]Syed Asad Alam
Winograd Convolution for Deep Neural Networks: Efficient Point Selection. ACM Trans. Embed. Comput. Syst. 21(6): 80:1-80:28 (2022) - [j35]Xiaowen Chu, Fausto Giunchiglia
Guest Editorial: Introduction to the Special Section on Communication-Efficient Distributed Machine Learning. IEEE Trans. Netw. Sci. Eng. 9(4): 1949-1950 (2022) - [c64]Muslim Chochlov, Gul Aftab Ahmed, James Vincent Patten
Using a Nearest-Neighbour, BERT-Based Approach for Scalable Clone Detection. ICSME 2022: 582-591 - [p1]Paul Biggar, David Gregg:
Building SSA in a Compiler for PHP. SSA-based Compiler Design 2022: 347-357 - [i27]Syed Asad Alam, Andrew Anderson, Barbara Barabasz, David Gregg:
Winograd Convolution for Deep Neural Networks: Efficient Point Selection. CoRR abs/2201.10369 (2022) - [i26]Syed Asad Alam, David Gregg, Giulio Gambardella, Michael Preußer, Michaela Blott:
On the RTL Implementation of FINN Matrix Vector Compute Unit. CoRR abs/2201.11409 (2022) - [i25]Kaveena Persand, Andrew Anderson, David Gregg:
Domino Saliency Metrics: Improving Existing Channel Saliency Metrics with Structural Information. CoRR abs/2205.02131 (2022) - [i24]Midia Reshadi, David Gregg:
LOCAL: Low-Complex Mapping Algorithm for Spatial DNN Accelerators. CoRR abs/2211.03672 (2022) - 2021
- [j34]Kaveena Persand
Taxonomy of Saliency Metrics for Channel Pruning. IEEE Access 9: 120110-120126 (2021) - [j33]Syed Asad Alam, James Garland
Low-precision Logarithmic Number Systems: Beyond Base-2. ACM Trans. Archit. Code Optim. 18(4): 47:1-47:25 (2021) - [c63]Kaveena Persand, Andrew Anderson, David Gregg:
Domino Saliency Metrics: Improving Existing Channel Saliency Metrics with Structural Information. AI*IA 2021: 447-461 - [c62]Midia Reshadi, David Gregg:
LOCAL: Low-Complex Mapping Algorithm for Spatial DNN Accelerators. NorCAS 2021: 1-7 - [i23]Syed Asad Alam, James Garland, David Gregg:
Low precision logarithmic number systems: Beyond base-2. CoRR abs/2102.06681 (2021) - 2020
- [j32]Miguel de Prado, Jing Su, Rabia Saeed, Lorenzo Keller, Noelia Vállez
Bonseyes AI Pipeline - Bringing AI to You: End-to-end integration of data, algorithms, and deployment tools. ACM Trans. Internet Things 1(4): 26:1-26:25 (2020) - [j31]Barbara Barabasz
Error Analysis and Improving the Accuracy of Winograd Convolution for Deep Neural Networks. ACM Trans. Math. Softw. 46(4): 37:1-37:33 (2020) - [c61]Syed Asad Alam
Beyond Base-2 Logarithmic Number Systems (WiP Paper). LCTES 2020: 141-145 - [c60]Andrew Anderson, Aravind Vasudevan, Cormac Keane, David Gregg:
High-Performance Low-Memory Lowering: GEMM-based Algorithms for DNN Convolution. SBAC-PAD 2020: 99-106 - [c59]Yuan Wen, Andrew Anderson, Valentin Radu
TASO: Time and Space Optimization for Memory-Constrained DNN Inference. SBAC-PAD 2020: 199-208 - [c58]Kaveena Persand, Andrew Anderson, David Gregg:
Composition of Saliency Metrics for Pruning with a Myopic Oracle. SSCI 2020: 753-759 - [i22]Andrew Anderson, Jing Su, Rozenn Dahyot
Performance-Oriented Neural Architecture Search. CoRR abs/2001.02976 (2020) - [i21]Kaveena Persand, Andrew Anderson, David Gregg:
Composition of Saliency Metrics for Channel Pruning with a Myopic Oracle. CoRR abs/2004.03376 (2020) - [i20]Yuan Wen, Andrew Anderson, Valentin Radu, Michael F. P. O'Boyle, David Gregg:
TASO: Time and Space Optimization for Memory-Constrained DNN Inference. CoRR abs/2005.10709 (2020) - [i19]Yuan Wen, David Gregg:
Exploiting Weight Redundancy in CNNs: Beyond Pruning and Quantization. CoRR abs/2006.11967 (2020) - [i18]James Garland, David Gregg:
HOBFLOPS CNNs: Hardware Optimized Bitsliced Floating-Point Operations Convolutional Neural Networks. CoRR abs/2007.06563 (2020)
2010 – 2019
- 2019
- [c57]Yuan Wen, Andrew Anderson, Valentin Radu
POSTER: Space and Time Optimal DNN Primitive Selection with Integer Linear Programming. PACT 2019: 489-490 - [c56]Barbara Barabasz, David Gregg:
Winograd Convolution for DNNs: Beyond Linear Polynomials. AI*IA 2019: 307-320 - [c55]Andrew Anderson, Michael Doyle, David Gregg:
Scalar Arithmetic Multiple Data: Customizable Precision for Deep Neural Networks. ARITH 2019: 61-68 - [c54]Andrew Anderson, Jing Su, Rozenn Dahyot
Performance-Oriented Neural Architecture Search. HPCS 2019: 177-184 - [i17]Barbara Barabasz, David Gregg:
Winograd Convolution for DNNs: Beyond linear polinomials. CoRR abs/1905.05233 (2019) - [i16]Kaveena Persand, Andrew Anderson, David Gregg:
A Taxonomy of Channel Pruning Signals in CNNs. CoRR abs/1906.04675 (2019) - 2018
- [j30]James Garland
Low Complexity Multiply-Accumulate Units for Convolutional Neural Networks with Weight-Sharing. ACM Trans. Archit. Code Optim. 15(3): 31:1-31:24 (2018) - [c53]Andrew Anderson
Optimal DNN primitive selection with partitioned boolean quadratic programming. CGO 2018: 340-351 - [i15]James Garland, David Gregg:
Low Complexity Multiply-Accumulate Units for Convolutional Neural Networks with Weight-Sharing. CoRR abs/1801.10219 (2018) - [i14]Barbara Barabasz, Andrew Anderson, David Gregg:
Improving accuracy of Winograd convolution for DNNs. CoRR abs/1803.10986 (2018) - [i13]Andrew Anderson, David Gregg:
Scalar Arithmetic Multiple Data: Customizable Precision for Deep Neural Networks. CoRR abs/1809.10572 (2018) - 2017
- [j29]James Garland
Low Complexity Multiply Accumulate Unit for Weight-Sharing Convolutional Neural Networks. IEEE Comput. Archit. Lett. 16(2): 132-135 (2017) - [j28]Andrew Anderson
Efficient Multibyte Floating Point Data Formats Using Vectorization. IEEE Trans. Computers 66(12): 2081-2096 (2017) - [c52]Aravind Vasudevan, Andrew Anderson
Parallel Multi Channel convolution using General Matrix Multiplication. ASAP 2017: 19-24 - [c51]Shixiong Xu, David Gregg:
Bitslice Vectors: A Software Approach to Customizable Data Precision on Processors with SIMD Extensions. ICPP 2017: 442-451 - [i12]Aravind Vasudevan, David Gregg:
Mutual Inclusivity of the Critical Path and its Partial Schedule on Heterogeneous Systems. CoRR abs/1701.08800 (2017) - [i11]Aravind Vasudevan, Andrew Anderson, David Gregg:
Parallel Multi Channel Convolution using General Matrix Multiplication. CoRR abs/1704.04428 (2017) - [i10]Andrew Anderson, Aravind Vasudevan, Cormac Keane, David Gregg:
Low-memory GEMM-based convolution algorithms for deep neural networks. CoRR abs/1709.03395 (2017) - [i9]Andrew Anderson, David Gregg:
Optimal DNN Primitive Selection with Partitioned Boolean Quadratic Programming. CoRR abs/1710.01079 (2017) - 2016
- [j27]Martin Marinov, Nicholas Nash, David Gregg:
Practical Algorithms for Finding Extremal Sets. ACM J. Exp. Algorithmics 21(1): 1.9:1-1.9:21 (2016) - [j26]Andrew Anderson, Avinash Malik, David Gregg:
Automatic Vectorization of Interleaved Data Revisited. ACM Trans. Archit. Code Optim. 12(4): 50:1-50:25 (2016) - [j25]Roman Atachiants, Gavin J. Doherty
Parallel Performance Problems on Shared-Memory Multicore Systems: Taxonomy and Observation. IEEE Trans. Software Eng. 42(8): 764-785 (2016) - [c50]Andrew Anderson
Vectorization of Multibyte Floating Point Data Formats. PACT 2016: 363-372 - [i8]Andrew Anderson, David Gregg:
Vectorization of Multibyte Floating Point Data Formats. CoRR abs/1601.07789 (2016) - [i7]Shixiong Xu, David Gregg:
Customizable Precision of Floating-Point Arithmetic with Bitslice Vector Types. CoRR abs/1602.04716 (2016) - [i6]James Garland, David Gregg:
Low Complexity Multiply Accumulate Unit for Weight-Sharing Convolutional Neural Networks. CoRR abs/1609.05132 (2016) - [i5]Maria Francesca, Arthur Hughes, David Gregg:
Spectral Convolution Networks. CoRR abs/1611.05378 (2016) - 2015
- [j24]Mircea Horea Ionica, David Gregg:
The Movidius Myriad Architecture's Potential for Scientific Computing. IEEE Micro 35(1): 6-14 (2015) - [j23]Avinash Malik, David Gregg:
Heuristics on Reachability Trees for Bicriteria Scheduling of Stream Graphs on Heterogeneous Multiprocessor Architectures. ACM Trans. Embed. Comput. Syst. 14(2): 23:1-23:26 (2015) - [c49]Shixiong Xu, David Gregg:
An Efficient Vectorization Approach to Nested Thread-level Parallelism for CUDA GPUs. PACT 2015: 488-489 - [c48]Shixiong Xu, David Gregg:
Exploiting Hyper-Loop Parallelism in Vectorization to Improve Memory Performance on CUDA GPGPU. TrustCom/BigDataSE/ISPA (3) 2015: 53-60 - [i4]Martin Marinov, David Gregg:
Towards Optimal Sorting Networks: The Third Level. CoRR abs/1502.04748 (2015) - [i3]Martin Marinov, David Gregg:
Sorting Networks: The Final Countdown. CoRR abs/1502.05983 (2015) - [i2]Martin Marinov, David Gregg:
Itemset Isomorphism: GI-Complete. CoRR abs/1507.05841 (2015) - [i1]Martin Marinov, Nicholas Nash, David Gregg:
Practical Algorithms for Finding Extremal Sets. CoRR abs/1508.01753 (2015) - 2014
- [c47]Roman Atachiants, David Gregg, Kim Jarvis, Gavin J. Doherty
Design considerations for parallel performance tools. CHI 2014: 2501-2510 - [c46]Aravind Vasudevan, Avinash Malik, David Gregg:
An improved simulated annealing heuristic for static partitioning of task graphs onto heterogeneous architectures. ICPADS 2014: 95-102 - [c45]Shixiong Xu, David Gregg:
Efficient Exploitation of Hyper Loop Parallelism in Vectorization. LCPC 2014: 382-396 - [c44]Shixiong Xu, David Gregg:
Semi-automatic Composition of Data Layout Transformations for Loop Vectorization. NPC 2014: 485-496 - 2013
- [j22]Mounira Bachir, Sid Ahmed Ali Touati, Frederic Brault, David Gregg, Albert Cohen:
Minimal Unroll Factor for Code Generation of Software Pipelining. Int. J. Parallel Program. 41(1): 1-58 (2013) - [j21]Jimmy Cleary, Owen Callanan, Mark Purcell, David Gregg:
Fast asymmetric thread synchronization. ACM Trans. Archit. Code Optim. 9(4): 27:1-27:22 (2013) - [j20]Stephen Dolan, Servesh Muralidharan, David Gregg:
Compiler support for lightweight context switching. ACM Trans. Archit. Code Optim. 9(4): 36:1-36:25 (2013) - [j19]Avinash Malik, David Gregg:
Orchestrating stream graphs using model checking. ACM Trans. Archit. Code Optim. 10(3): 19:1-19:25 (2013) - [c43]Servesh Muralidharan, Aravind Vasudevan, Avinash Malik, David Gregg:
Heterogeneous Multiconstraint Application Partitioner (HMAP). TrustCom/ISPA/IUCC 2013: 999-1007 - [c42]Servesh Muralidharan, Kevin Casey, David Gregg:
A Parallel Runtime Framework for Communication Intensive Stream Applications. TrustCom/ISPA/IUCC 2013: 1179-1187 - 2012
- [j18]Paul Biggar, Edsko de Vries, David Gregg:
A practical solution for achieving language compatibility in scripting language compilers. Sci. Comput. Program. 77(9): 971-989 (2012) - [j17]Jason McCandless, David Gregg:
Compiler techniques to improve dynamic branch prediction for indirect jump and call instructions. ACM Trans. Archit. Code Optim. 8(4): 24:1-24:20 (2012) - [c41]Mark Purcell, Aravind Vasudevan, David Gregg:
Real-Time Sensor Signal Capture from a Harsh Environment. DS-RT 2012: 36-43 - 2011
- [c40]Jason McCandless, David Gregg:
Optimizing interpreters by tuning opcode orderings on virtual machines for modern architectures: or: how I learned to stop worrying and love hill climbing. PPPJ 2011: 161-170 - 2010
- [j16]Nicholas Nash, David Gregg:
An output sensitive algorithm for computing a maximum independent set of a circle graph. Inf. Process. Lett. 110(16): 630-634 (2010) - [j15]Nicholas Nash, David Gregg:
Comparing integer data structures for 32- and 64-bit keys. ACM J. Exp. Algorithmics 15 (2010) - [j14]Milan Tichý, Jan Schier, David Gregg:
GSFAP adaptive filtering using log arithmetic for resource-constrained embedded systems. ACM Trans. Embed. Comput. Syst. 9(3): 29:1-29:31 (2010) - [c39]Raymond Manley, Paul Magrath, David Gregg:
Code generation for hardware accelerated AES. ASAP 2010: 345-348 - [c38]Kevin Williams, Jason McCandless, David Gregg:
Dynamic interpretation for dynamic scripting languages. CGO 2010: 278-287 - [c37]Raymond Manley, David Gregg:
A Program Generator for Intel AES-NI Instructions. INDOCRYPT 2010: 311-327
2000 – 2009
- 2009
- [c36]Mark Purcell, Owen Callanan, David Gregg:
Streamlining Offload Computing to High Performance Architectures. ICCS (1) 2009: 974-983 - [c35]Raymond Manley, David Gregg:
Mapping Streaming Languages to General Purpose Processors through Vectorization. LCPC 2009: 95-110 - [c34]Mounira Bachir, David Gregg, Sid Ahmed Ali Touati:
Using the Meeting Graph Framework to Minimise Kernel Loop Unrolling for Scheduled Loops. LCPC 2009: 278-292 - [c33]Kevin Williams, Jason McCandless, David Gregg:
Portable Just-in-Time Specialization of Dynamically Typed Scripting Languages. LCPC 2009: 391-398 - [c32]Paul Biggar, Edsko de Vries, David Gregg:
A practical solution for scripting language compilers. SAC 2009: 1916-1923 - 2008
- [j13]Paul Biggar, Nicholas Nash, Kevin Williams, David Gregg:
An experimental study of sorting and branch prediction. ACM J. Exp. Algorithmics 12: 1.8:1-1.8:39 (2008) - [j12]Nicholas Nash, Sylvain Lelait, David Gregg:
Efficiently implementing maximum independent set algorithms on circle graphs. ACM J. Exp. Algorithmics 13 (2008) - [j11]Yunhe Shi, Kevin Casey, M. Anton Ertl, David Gregg:
Virtual machine showdown: Stack versus registers. ACM Trans. Archit. Code Optim. 4(4): 2:1-2:36 (2008) - [j10]Emre Özer, Andy Nisbet, David Gregg:
A stochastic bitwidth estimation technique for compact and low-power custom processors. ACM Trans. Embed. Comput. Syst. 7(3): 34:1-34:30 (2008) - [c31]Kevin Williams, Albert Noll, Andreas Gal, David Gregg:
Optimization strategies for a java virtual machine interpreter on the cell broadband engine. Conf. Computing Frontiers 2008: 189-198 - [c30]Nicholas Nash, David Gregg:
Comparing Integer Data Structures for 32 and 64 Bit Keys. WEA 2008: 28-42 - [e2]David Gregg, Vikram S. Adve, Brian N. Bershad:
Proceedings of the 4th International Conference on Virtual Execution Environments, VEE 2008, Seattle, WA, USA, March 5-7, 2008. ACM 2008, ISBN 978-1-59593-796-4 [contents] - 2007
- [j9]Kevin Casey, M. Anton Ertl, David Gregg:
Optimizing indirect branch prediction accuracy in virtual machine interpreters. ACM Trans. Program. Lang. Syst. 29(6): 37 (2007) - [c29]David Gregg, Colm McSweeney, Ciarán McElroy, Fergal Connor, Séamas McGettrick, David Moloney, Dermot Geraghty:
FPGA based Sparse Matrix Vector Multiplication using Commodity DRAM Memory. FPL 2007: 786-791 - 2006
- [j8]David Gregg, M. Anton Ertl:
Optimizing code-copying JIT compilers for virtual stack machines. Concurr. Comput. Pract. Exp. 18(11): 1465-1484 (2006) - [j7]Yunhe Shi, Emre Özer, David Gregg:
Analyzing Effects of Trace Cache Configurations on the Prediction of Indirect Branches. J. Instr. Level Parallelism 8 (2006) - [c28]Milan Tichý, Jan Schier, David Gregg:
Efficient Floating-Point Implementation of High-Order (N)LMS Adaptive Filters in FPGA. ARC 2006: 311-316 - [c27]Milan Tichý, Andy Nisbet, David Gregg:
GSFAP adaptive filtering using log arithmetic for resource-constrained embedded systems. FPGA 2006: 236 - [c26]Owen Callanan, David Gregg, Andy Nisbet, Mike Peardon:
High Performance Scientific Computing Using FPGAs with IEEE Floating Point and Logarithmic Arithmetic for Lattice QCD. FPL 2006: 1-6 - [c25]Yunhe Shi, Emre Özer, David Gregg:
Low-Cost Microarchitectural Techniques for Enhancing the Prediction of Return Addresses on High-Performance Trace Cache Processors. ISCIS 2006: 248-257 - [c24]M. Anton Ertl, Kevin Casey, David Gregg:
Fast and flexible instruction selection with on-demand tree-parsing automata. PLDI 2006: 52-60 - [c23]Milan Tichý, Jan Schier, David Gregg:
FPGA Implementation of Adaptive Filters based on GSFAP using Log Arithmetic. SiPS 2006: 321-326 - 2005
- [j6]David Gregg, James F. Power
A method-level comparison of the Java Grande and SPEC JVM98 benchmark suites. Concurr. Pract. Exp. 17(7-8): 757-773 (2005) - [j5]Emre Özer, Andy Nisbet, David Gregg, Owen Callanan:
Estimating data bus size for custom processors in embedded systems. Des. Autom. Embed. Syst. 10(1): 5-26 (2005) - [j4]David Gregg, Andrew Beatty, Kevin Casey, Brian Davis, Andy Nisbet:
The case for virtual register machines. Sci. Comput. Program. 57(3): 319-338 (2005) - [c22]Kevin Casey, David Gregg, M. Anton Ertl:
Tiger - An Interpreter Generation Tool. CC 2005: 246-249 - [c21]Libero Ficocelli, David Gregg:
B.Sc. Computer Game Development ... Why not? DiGRA Conference 2005 - [c20]Owen Callanan, Andy Nisbet, Emre Özer, James Sexton, David Gregg:
FPGA Implementation of a Lattice Quantum Chromodynamics Algorithm Using Logarithmic Arithmetic. IPDPS 2005 - [c19]Emre Özer, Resit Sendag, David Gregg:
Multiple-Valued Caches for Power-Efficient Embedded Systems. ISMVL 2005: 126-131 - [c18]Yunhe Shi, David Gregg, Andrew Beatty, M. Anton Ertl:
Virtual machine showdown: stack versus registers. VEE 2005: 153-163 - 2004
- [c17]M. Anton Ertl, David Gregg:
Retargeting JIT Compilers by using C-Compiler Generated Executable Code. IEEE PACT 2004: 41-50 - [c16]Emre Özer, Andy Nisbet, David Gregg:
Stochastic Bit-Width Approximation Using Extreme Value Theory for Customizable Processors. CC 2004: 250-264 - [c15]Emre Özer, Andy Nisbet, David Gregg:
Automatic Customization of Embedded Applications for Enhanced Performance and Reduced Power Using Optimizing Compiler Techniques. Euro-Par 2004: 318-327 - [c14]Emre Özer, Andy Nisbet, David Gregg:
Fine-Tuning Loop-Level Parallelism for Increasing Performance of DSP Applications on FPGAs. FCCM 2004: 273-274 - [c13]M. Anton Ertl, David Gregg:
Combining stack caching with dynamic superinstructions. IVME 2004: 7-14 - 2003
- [j3]David Gregg, James F. Power, John Waldron:
Platform independent dynamic Java virtual machine analysis: the Java Grande Forum benchmark suite. Concurr. Comput. Pract. Exp. 15(3-5): 459-484 (2003) - [j2]M. Anton Ertl, David Gregg:
The Structure and Performance of Efficient Interpreters. J. Instr. Level Parallelism 5 (2003) - [c12]David Gregg, M. Anton Ertl:
A Language and Tool for Generating Efficient Virtual Machine Interpreters. Domain-Specific Program Generation 2003: 196-215 - [c11]Brian Davis, Andrew Beatty, Kevin Casey, David Gregg, John Waldron:
The case for virtual register machines. IVME 2003: 41-49 - [c10]M. Anton Ertl, David Gregg:
Optimizing indirect branch prediction accuracy in virtual machine interpreters. PLDI 2003: 278-288 - [c9]Andrew Beatty, Kevin Casey, David Gregg, Andrew Nisbet:
An Optimized Java Interpreter for Connected Devices and Embedded Systems. SAC 2003: 692-697 - [c8]Kevin Casey, David Gregg, M. Anton Ertl, Andrew Nisbet:
Towards Superinstructions for Java Interpreters. SCOPES 2003: 329-343 - [e1]David Gregg, M. Anton Ertl:
Proceedings of the 2003 Workshop on Interpreters, Virtual Machines and Emulators, IVME 2003, San Diego, California, USA, June 12, 2003. ACM 2003, ISBN 978-1-58113-655-5 [contents] - 2002
- [j1]M. Anton Ertl, David Gregg, Andreas Krall, Bernd Paysan:
Vmgen - a generator of efficient virtual machine interpreters. Softw. Pract. Exp. 32(3): 265-294 (2002) - [c7]M. Anton Ertl, David Gregg:
Building an Interpreter with Vmgen. CC 2002: 5-8 - [c6]David Gregg, James F. Power, John Waldron:
Measuring the impact of object-oriented techniques in grande applications: a method-level analysis. Java Grande 2002: 229 - 2001
- [c5]David Gregg:
Comparing Tail Duplication with Compensation Code in Single Path Global Instruction Scheduling. CC 2001: 200-212 - [c4]M. Anton Ertl, David Gregg:
The Behavior of Efficient Virtual Machine Interpreters on Modern Architectures. Euro-Par 2001: 403-412 - [c3]David Gregg, M. Anton Ertl, Andreas Krall:
Implementing an Efficient Java Interpreter. HPCN Europe 2001: 613-620 - [c2]John Waldron, David Gregg:
Identification and Quantification of Hotspots in Java Grande Programs. HPCN Europe 2001: 701-710 - 2000
- [c1]David Gregg:
Global Software Pipelining with Iteration Preselection. CC 2000: 189-201
Coauthor Index
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