20 results for “compute”
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Harshita Gupta, Mayank Kabra, Jaewoo Park, Priyam Mehta +8 more
The paper characterizes Homomorphic Encryption (HE) operations on a real-world Processing-In-Memory (PIM) system, demonstrating that while PIM is a viable alternative to CPUs/GPUs, performance is limi…
Hawkeye is a system that allows perfect, precision-preserving reproduction of GPU-level matrix multiplication operations on a CPU, enabling efficient and trustworthy third-party auditing of machine le…
This paper presents a method for compressing matrices using a RePair straight-line program (SLP), allowing matrix-vector products with time and space proportional to the compressed size, and demonstra…
The paper introduces Grid Programs, a novel, Turing-complete model of computation where programs are two-dimensional arrangements of instructions, fundamentally departing from linear code structures.
Yihan Wang, Huiru Yan, Luxin Zhang, Long Cheng +5 more
The paper proposes a framework to harvest unused computation resources on AI chips for general-purpose tasks using neural architecture search and approximation techniques.
This paper compares three neuromorphic core designs for handling weight sparsity in event-driven neural networks and quantifies the performance and energy costs.
O-POPE is a novel outer-product engine that accelerates floating-point GEMM by repurposing FPU pipeline registers as buffers, achieving high utilization and improved energy efficiency.
The paper proposes a fine-grained approach to overlap expert compute with the second all-to-all communication in Mixture-of-Experts (MoE) models, improving distributed MoE execution efficiency on mult…
Hyunwoo Oh, Suyeon Jang, Hanning Chen, Sanggeon Yun +2 more
The paper presents ExaGEMM, a framework for designing and exploring CPU-native low-bit GEMM via register-resident LUT execution.
Afzal Ahmad, Gaoyu Mao, Shoubo Hu, Hui-Ling Zhen +3 more
A co-designed hardware-software approach for task-conditional sparsity in multi-task inference models, reducing FLOPs, latency, and energy.
The paper proposes a novel space switching method to efficiently unify arithmetic and comparison operations within Fully Homomorphic Encryption (FHE) schemes, achieving significant performance improve…
Jianan Mu, Ge Yu, Tenghui Hua, Liang Kong +5 more
This paper presents an efficient fault-tolerance scheme for CPU-based fully homomorphic encryption (FHE) that reduces protection overhead and achieves 100 percent detection rate under random single-bi…
An R package named rush is introduced, which provides a shared-state coordination layer for asynchronously parallelized iterative algorithms using a Redis database.
Turning off automatic NUMA balancing in simulation of large-scale spiking networks reduces energy consumption by 30%.