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- Mohammad Ashraful Anam, Yiannis Andreopoulos
- IEEE Trans. Multimedia
- 2012

Convolution and cross-correlation are the basis of filtering and pattern or template matching in multimedia signal processing. We propose two throughput scaling options for any one-dimensional convolution kernel in programmable processors by adjusting the imprecision (distortion) of computation. Our approach is based on scalar quantization, followed by two… (More)

The generic matrix multiply (GEMM) routine comprises the compute and memory-intensive part of many information retrieval, relevance ranking and object recognition systems. Because of the prevalence of GEMM in these applications, ensuring its robustness to transient hardware faults is of paramount importance for highly-efficient/highly-reliable systems. This… (More)

- Mohammad Ashraful Anam, Paul N. Whatmough, Yiannis Andreopoulos
- IEEE Trans. Circuits Syst. Video Techn.
- 2014

Generic matrix multiplication (GEMM) and onedimensional convolution/cross-correlation (CONV) kernels often constitute the bulk of the computeand memory-intensive processing within image/audio recognition and matching systems. We propose a novel method to scale the energy and processing throughput of GEMM and CONV kernels for such error-tolerant multimedia… (More)

- Joseph Doyle, Vasileios Giotsas, Mohammad Ashraful Anam, Yiannis Andreopoulos
- 2016 IEEE International Conference on Cloud…
- 2016

Computation-as-a-Service (CaaS) offerings have gained traction in the last few years due to their effectiveness in balancing between the scalability of Software-as-a-Service and the customisation possibilities of Infrastructure-as-a-Service platforms. To function effectively, a CaaS platform must have three key properties: (i) reactive assignment of… (More)

- Mohammad Ashraful Anam, Yiannis Andreopoulos
- IOLTS
- 2015

A new roll-forward technique is proposed that recovers from any single fail-stop failure in M integer data streams (M ≥ 3) when undergoing linear, sesquilinear or bijective (LSB) operations, such as: scaling, additions/subtractions, inner or outer vector products and permutations. In the proposed approach, the M input integer data streams are linearly… (More)

- Mohammad Ashraful Anam, Paul N. Whatmough, Yiannis Andreopoulos
- The 11th IEEE Symposium on Embedded Systems for…
- 2013

Generic matrix multiplication (GEMM) and one-dimensional discrete convolution/cross-correlation (CONV) kernels perform the bulk of the compute- and memory-intensive processing within image/audio recognition and matching systems. We propose a novel method to scale the energy and processing throughput of GEMM and CONV kernels for such error-tolerant… (More)

The generic matrix multiply (GEMM) routine comprises the compute and memory-intensive part of many information retrieval, machine learning and object recognition systems that process integer inputs. Therefore, it is of paramount importance to ensure that integer GEMM computations remain robust to silent data corruptions (SDCs), which stem from accidental… (More)

We present Dithen, a novel computation-as-a-service (CaaS) cloud platform specifically tailored to the parallel execution of large-scale multimedia tasks. Dithen handles the upload/download of both multimedia data and executable items, the assignment of compute units to multimedia workloads, and the reactive control of the available compute units to… (More)

- Mohammad Ashraful Anam, Yiannis Andreopoulos
- IEEE Transactions on Signal Processing
- 2016

A new technique is proposed for fault-tolerant linear, sesquilinear and bijective (LSB) operations on M integer data streams (M ≥ 3), such as: scaling, additions/subtractions, inner or outer vector products, permutations and convolutions. In the proposed method, M input integer data streams are linearly superimposed to form M numerically-entangled… (More)

We propose a new technique for the mitigation of fail-stop failures and/or silent data corruptions (SDCs) within linear, sesquilinear or bijective (LSB) operations on M integer data streams (M ≥ 3). In the proposed approach, the M input streams are linearly superimposed to form M numerically entangled integer data streams that are stored in-place of the… (More)

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