this T-Platforms

Rendering resourcesCode parallelizationT-Platforms is offering rendering services tocompanies specializing in 3D graphics andanimation. Large and medium sized productionstudios can lease a specific rendering farm toproduce 3D graphics on-site. Access to a 50-node dual-socket Intel Xeon quad-core renderingfarm, based on T-Blade 1.1 systems, is providedeither through secure internet protocol ordelivered fully configured and debugged to thecustomer’s premises.Many high performance computing systems utilize NVIDIA Teslaaccelerators, based on GF1x0 GPUs. TB2-TL, T-Blade V-Class andT-Mini P-Class systems support one or two accelerators in each node.Accelerators help to reach previously unattainable performance forapplications running in dual precision mode. This results in a reductionof node count, runtime, and OpEx related to cooling, power andservice. And yet not that many applications today support GPU-basedaccelerators to enjoy the savings.Typical GPU-based computing implementation issues are:26Available hardware• A single rack cabinet with 12-20 nodes based onthe six-core Intel Xeon 56xx series and AMD 12-coreOpteron 61xx series platform architecture, witha QDR Infiniband interconnect and an Ethernetbasednetwork, complemented by Panasas and LSIEngenio parallel storage systems.• 50-node dual-socket Intel Xeon quad-core renderingfarm, based on T-Blade 1.1 systems and theT-Store ActiveStore parallel file system with 12TB ofstorage or more for centralized data access.• Depending on the complexity and timing ofa specific project, remote access to largerconfigurations can be provided as well.• A substantial time is required for programmers to develop or adaptapplication code• Absence of developer experience for parallel computations• Inconsistencies between CUDA and OpenCL libraries, developed for varioushardware platforms• Performance optimization is limited by the adaption of softwarefor the specific hardware of the systemTo address these issues T-Platforms is offering services to portapplications to massively parallel heterogeneous platforms. Dependingon the system configuration, from 512 to 1024 compute cores ofNVIDIA GF1x0 are present on every node to help achieve a substantialincrease of available computing power on parallel codes.Services:■■Adapting applications for GPU architecture■■Optimization of CUDA programs■■MPU and OpenMP porting to NVIDIA CUDA■■CUDA code development for serial code■■Consulting support■■Support to transfer algorithms to GPU architecture■■Technical support on CUDA and OpenCL-related issues■■Assistance on existing code integration issues, associated with thenew technologies■■System utilities to simplify CUDA and OpenCL programmingT-Platforms | One-stop source for petascale computing