Zobrazeno 1 - 10
of 303
pro vyhledávání: '"Vijaykumar, T."'
Emerging machine learning (ML) models (e.g., transformers) involve memory pin bandwidth-bound matrix-vector (MV) computation in inference. By avoiding pin crossings, processing in memory (PIM) can improve performance and energy for pin-bound workload
Externí odkaz:
http://arxiv.org/abs/2404.04708
Memory consistency model (MCM) issues in out-of-order-issue microprocessor-based shared-memory systems are notoriously non-intuitive and a source of hardware design bugs. Prior hardware verification work is limited to in-order-issue processors, to pr
Externí odkaz:
http://arxiv.org/abs/2404.03113
Spectre attacks exploit microprocessor speculative execution to read and transmit forbidden data outside the attacker's trust domain and sandbox. Recent hardware schemes allow potentially-unsafe speculative accesses but prevent the secret's transmiss
Externí odkaz:
http://arxiv.org/abs/2306.07785
Convolutional neural networks (CNNs) are emerging as powerful tools for image processing in important commercial applications. We focus on the important problem of improving the latency of image recognition. CNNs' large data at each layer's input, fi
Externí odkaz:
http://arxiv.org/abs/2106.14138
Convolutional neural networks (CNNs) are emerging as powerful tools for visual recognition. Recent architecture proposals for sparse CNNs exploit zeros in the feature maps and filters for performance and energy without losing accuracy. Sparse archite
Externí odkaz:
http://arxiv.org/abs/2104.08734
We propose Booster, a novel accelerator for gradient boosting trees based on the unique characteristics of gradient boosting models. We observe that the dominant steps of gradient boosting training (accounting for 90-98% of training time) involve sim
Externí odkaz:
http://arxiv.org/abs/2011.02022
Autor:
Xue, Jiachen, Chaudhry, Muhammad Usama, Vamanan, Balajee, Vijaykumar, T. N., Thottethodi, Mithuna
Though Remote Direct Memory Access (RDMA) promises to reduce datacenter network latencies significantly compared to TCP (e.g., 10x), end-to-end congestion control in the presence of incasts is a challenge. Targeting the full generality of the congest
Externí odkaz:
http://arxiv.org/abs/1805.11158
Autor:
Chang, Yiyang, Rezaei, Ashkan, Vamanan, Balajee, Hasan, Jahangir, Rao, Sanjay, Vijaykumar, T. N.
The conventional approach to scaling Software Defined Networking (SDN) controllers today is to partition switches based on network topology, with each partition being controlled by a single physical controller, running all SDN applications. However,
Externí odkaz:
http://arxiv.org/abs/1609.07192
With the imminent slowing down of DRAM scaling, Phase Change Memory (PCM) is emerging as a lead alternative for main memory technology. While PCM achieves low energy due to various technology-specific advantages, PCM is significantly slower than DRAM
Externí odkaz:
http://arxiv.org/abs/1504.04297
Datacenters running on-line, data-intensive applications (OLDIs) consume significant amounts of energy. However, reducing their energy is challenging due to their tight response time requirements. A key aspect of OLDIs is that each user query goes to
Externí odkaz:
http://arxiv.org/abs/1503.05338