Detailed knowledge of hydrocarbon fuel combustion chemistry has grown tremendously in recent years. However, the gap between detailed chemistry and computational fluid dynamics (CFD) remains, because of the high cost of solving detailed chemistry in a large number of computational cells. This paper presents the results of applying a suite of techniques aimed at closing this gap. The techniques include use of a surrogate blend optimizer and a guided mechanism reduction methodology, as well as advanced methods for efficiently and accurately coupling the pre-reduced kinetic models with the multidimensional transport equations. The advanced methods include dynamic adaptive chemistry (DAC) and dynamic cell clustering (DCC) algorithms. These techniques are demonstrated by determining a multi-component diesel fuel surrogate mechanism, reducing it as appropriate for the conditions of interest, and then employing the reduced (but still quite detailed) mechanism in a multidimensional CFD calculation of diesel engine combustion. The CFD simulation employs the newly developed FORTÉ simulation package, which was designed to take advantage of the advanced chemistry solver methodologies as well as advanced spray models. We start with a detailed diesel-surrogate mechanism that contains 26 model-fuel components, for which an extensive set of validation studies have been performed to verify predictions of ignition-delay and flame properties. The diesel surrogate mechanism contains ~3,800 species and ~16,000 reactions. Given the cetane number and physical properties of a specific blend of diesel fuel, a surrogate-blend optimizer was used to obtain multi-component diesel surrogates that match the properties of the diesel. With this diesel surrogate composition, a guided mechanism reduction method was used to reduce the 3,800-species diesel mechanism to a 437-species mechanism, maintaining accuracy of fundamental predictions over a wide range of conditions. Then the 437-species mechanism was used directly in a CFD simulation of diesel engine combustion using a sector mesh. The combined use of the DAC and DCC methods offers a speed-up factor of two to three orders of magnitude compared to conventional computational approaches, making the once-prohibitive computational task achievable within a reasonable time frame. Calculated in-cylinder pressure, heat release rates, and emissions were analyzed against experimental data. The chemistry solution techniques demonstrated in this paper prove highly efficient and accurate, and they pave the way for including sophisticated combustion kinetics in computational engine combustion research.