David Gregg

David Gregg, Kevin Casey, Servesh Muralidharan, 2013, 2013 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications.

Automatic Vectorization of Interleaved Data Revisited

David Gregg, Avinash Malik, Andrew Anderson, 2015, ACM Trans. Archit. Code Optim..

EC-Crypto: Highly Efficient Area-Delay Optimized Elliptic Curve Cryptography Processor

David Gregg, Khalid Javeed, A. El-Moursy, 2023, IEEE Access.

High‐speed parallel reconfigurable Fp multipliers for elliptic curve cryptography applications

David Gregg, Khalid Javeed, Kamran Saeed, 2022, Int. J. Circuit Theory Appl..

Winograd Convolution for Deep Neural Networks: Efficient Point Selection

David Gregg, Andrew Anderson, Syed Asad Alam, 2022, ACM Trans. Embed. Comput. Syst..

Common Practices in Fixing Open Source Related Vulnerabilities

David Gregg, J. Buckley, Muslim Chochlov, 2023 .

An Efficient Vectorization Approach to Nested Thread-level Parallelism for CUDA GPUs

David Gregg, Shixiong Xu, David Gregg, 2015, 2015 International Conference on Parallel Architecture and Compilation (PACT).

Virtual machine showdown: stack versus registers

M. Ertl, David Gregg, Yunhe Shi, 2005, VEE '05.

Orchestrating stream graphs using model checking

David Gregg, Avinash Malik, David Gregg, 2013, ACM Trans. Archit. Code Optim..

High Performance Scientific Computing Using FPGAs with IEEE Floating Point and Logarithmic Arithmetic for Lattice QCD

David Gregg, Mike Peardon, Andy Nisbet, 2006, 2006 International Conference on Field Programmable Logic and Applications.

Parallel Multi Channel convolution using General Matrix Multiplication

David Gregg, Andrew Anderson, Aravind Vasudevan, 2017, 2017 IEEE 28th International Conference on Application-specific Systems, Architectures and Processors (ASAP).

High-Performance Low-Memory Lowering: GEMM-based Algorithms for DNN Convolution

David Gregg, Andrew Anderson, Aravind Vasudevan, 2020, 2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD).

Sorting in the Presence of Branch Prediction and Caches Fast Sorting on Modern Computers

David Gregg, Paul Biggar, David Gregg, 2005 .

Scalar Arithmetic Multiple Data: Customizable Precision for Deep Neural Networks

David Gregg, Andrew Anderson, David Gregg, 2018, 2019 IEEE 26th Symposium on Computer Arithmetic (ARITH).

Parallel Performance Problems on Shared-Memory Multicore Systems: Taxonomy and Observation

David Gregg, Gavin J. Doherty, Roman Atachiants, 2016, IEEE Transactions on Software Engineering.

Comparing integer data structures for 32- and 64-bit keys

David Gregg, Nicholas Nash, David Gregg, 2010, JEAL.

Compiler support for lightweight context switching

David Gregg, Servesh Muralidharan, Stephen Dolan, 2013, TACO.

Heterogeneous Multiconstraint Application Partitioner (HMAP)

David Gregg, Avinash Malik, Servesh Muralidharan, 2013, 2013 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications.

Maple: A Processing Element for Row-Wise Product Based Sparse Tensor Accelerators

David Gregg, M. Reshadi, 2023, ArXiv.

Winograd Convolution for DNNs: Beyond Linear Polynomials pdf

David Gregg, Barbara Barabasz, David Gregg, 2019, AI*IA.

Error Analysis and Improving the Accuracy of Winograd Convolution for Deep Neural Networks

David Gregg, Andrew Anderson, Kirk M. Soodhalter, 2018, ACM Trans. Math. Softw..

Low-memory GEMM-based convolution algorithms for deep neural networks pdf

David Gregg, Andrew Anderson, Aravind Vasudevan, 2017, ArXiv.

Analyzing Effects of Trace Cache Configurations on the Prediction of Indirect Branches

David Gregg, Yunhe Shi, Emre Özer, 2006, J. Instr. Level Parallelism.

Optimizing interpreters by tuning opcode orderings on virtual machines for modern architectures: or: how I learned to stop worrying and love hill climbing

David Gregg, Jason McCandless, David Gregg, 2011, PPPJ.

Retargeting JIT compilers by using C-compiler generated executable code

David Gregg, M. Anton Ertl, M. Ertl, 2004, Proceedings. 13th International Conference on Parallel Architecture and Compilation Techniques, 2004. PACT 2004..

Low-precision Logarithmic Number Systems

David Gregg, Syed Asad Alam, James Garland, 2021, ACM Trans. Archit. Code Optim..

On the RTL Implementation of FINN Matrix Vector Unit

Thomas B. Preußer, Syed Asad Alam, David Gregg, 2022, ACM Transactions on Embedded Computing Systems.

Taxonomy of Saliency Metrics for Channel Pruning

David Gregg, Kaveena Persand, Andrew Anderson, 2019, IEEE Access.

Multiple-valued logic buses for reducing bus energy in low-power systems

Resit Sendag, Emre Ozer, David Gregg, 2006 .

Estimating data bus size for custom processors in embedded systems

David Gregg, Emre Özer, Andy Nisbet, 2005, Des. Autom. Embed. Syst..

Towards Superinstructions for Java Interpreters

David Gregg, Andy Nisbet, Kevin Casey, 2003, SCOPES.

Benchmarking the Java Virtual Architecture

David Gregg, James F. Power, John Waldron, 2002 .

TASO: Time and Space Optimization for Memory-Constrained DNN Inference

David Gregg, Andrew Anderson, Yuan Wen, 2020, 2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD).

Low Complexity Multiply-Accumulate Units for Convolutional Neural Networks with Weight-Sharing

David Gregg, James Garland, David Gregg, 2018, ACM Trans. Archit. Code Optim..

Low Complexity Multiply Accumulate Unit for Weight-Sharing Convolutional Neural Networks

David Gregg, James Garland, David Gregg, 2016, IEEE Computer Architecture Letters.

Performance-Oriented Neural Architecture Search

David Gregg, Rozenn Dahyot, Jing Su, 2019, 2019 International Conference on High Performance Computing & Simulation (HPCS).

Exploiting Weight Redundancy in CNNs: Beyond Pruning and Quantization pdf

David Gregg, Yuan Wen, David Gregg, 2020, ArXiv.