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ASM: An Adaptive Secure Multicore for Co-located Mutually Distrusting Processes
With the ever-increasing virtualization of software and hardware, the privacy of user-sensitive data is a fundamental concern in computation outsourcing. Secure processors enable a trusted execution environment to guarantee security properties based on ...
Jointly Optimizing Job Assignment and Resource Partitioning for Improving System Throughput in Cloud Datacenters
Colocating multiple jobs on the same server has been widely applied for improving resource utilization in cloud datacenters. However, the colocated jobs would contend for the shared resources, which could lead to significant performance degradation. An ...
Accelerating Convolutional Neural Network by Exploiting Sparsity on GPUs
The convolutional neural network (CNN) is an important deep learning method, which is widely used in many fields. However, it is very time consuming to implement the CNN where convolution usually takes most of the time. There are many zero values in ...
GraphTune: An Efficient Dependency-Aware Substrate to Alleviate Irregularity in Concurrent Graph Processing
- Jin Zhao,
- Yu Zhang,
- Ligang He,
- Qikun Li,
- Xiang Zhang,
- Xinyu Jiang,
- Hui Yu,
- Xiaofei Liao,
- Hai Jin,
- Lin Gu,
- Haikun Liu,
- Bingsheng He,
- Ji Zhang,
- Xianzheng Song,
- Lin Wang,
- Jun Zhou
With the increasing need for graph analysis, massive Concurrent iterative Graph Processing (CGP) jobs are usually performed on the common large-scale real-world graph. Although several solutions have been proposed, these CGP jobs are not coordinated with ...
The Impact of Page Size and Microarchitecture on Instruction Address Translation Overhead
As the volume of data processed by applications has increased, considerable attention has been paid to data address translation overheads, leading to the widespread use of larger page sizes (“superpages”) and multi-level translation lookaside buffers (...
Cache Programming for Scientific Loops Using Leases
- Benjamin Reber,
- Matthew Gould,
- Alexander H. Kneipp,
- Fangzhou Liu,
- Ian Prechtl,
- Chen Ding,
- Linlin Chen,
- Dorin Patru
Cache management is important in exploiting locality and reducing data movement. This article studies a new type of programmable cache called the lease cache. By assigning leases, software exerts the primary control on when and how long data stays in the ...
MPU: Memory-centric SIMT Processor via In-DRAM Near-bank Computing
With the growing number of data-intensive workloads, GPU, which is the state-of-the-art single-instruction-multiple-thread (SIMT) processor, is hindered by the memory bandwidth wall. To alleviate this bottleneck, previously proposed 3D-stacking near-bank ...
rNdN: Fast Query Compilation for NVIDIA GPUs
GPU database systems are an effective solution to query optimization, particularly with compilation and data caching. They fall short, however, in end-to-end workloads, as existing compiler toolchains are too expensive for use with short-running queries. ...
Hierarchical Model Parallelism for Optimizing Inference on Many-core Processor via Decoupled 3D-CNN Structure
The tremendous success of convolutional neural network (CNN) has made it ubiquitous in many fields of human endeavor. Many applications such as biomedical analysis and scientific data analysis involve analyzing volumetric data. This spawns huge demand for ...
MFFT: A GPU Accelerated Highly Efficient Mixed-Precision Large-Scale FFT Framework
Fast Fourier transform (FFT) is widely used in computing applications in large-scale parallel programs, and data communication is the main performance bottleneck of FFT and seriously affects its parallel efficiency. To tackle this problem, we propose a ...
Approx-RM: Reducing Energy on Heterogeneous Multicore Processors under Accuracy and Timing Constraints
Reducing energy consumption while providing performance and quality guarantees is crucial for computing systems ranging from battery-powered embedded systems to data centers. This article considers approximate iterative applications executing on ...