Mohammad Ashraful Anam

Learn More
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)
—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 bijec-tive (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)
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)
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 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)
—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 C 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)
—Generic matrix multiplication (GEMM) and one-dimensional convolution/cross-correlation (CONV) kernels often constitute 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)
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)
  • 1